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By Ken Stibler; Powered by Reyvism

What work is AI enabling you to avoid?

What work is AI enabling you to avoid?

Using AI is becoming a very respectable way not to do work.

A piece of analysis needs writing, a spreadsheet needs cleaning up or a review needs drafting. Instead comes the search for a tool, the prompt, the second prompt, the documentation, the correction and eventually the explanation for why the model still cannot quite produce what was needed. An hour disappears, 4 drafts are available, but the original task remains.

Some of this is sensible investment. Nobody complains about spending an afternoon automating something that saves a day every month. The more interesting cases are the ones in which learning to use the tool becomes a substitute for doing the work. AI makes that unusually easy because experimentation carries none of the stigma of ordinary procrastination. Wrestling with a model looks like capability building.

Companies are also giving employees plenty of reason to wrestle. In on survey of finance leaders, 76% reported high or very high pressure to fully implement AI, and respondents spent an average 26% of their workday verifying or correcting finance-specific AI output.

Management work is particularly vulnerable. Seventy-eight percent of people managers surveyed by Highwire had used AI for feedback or performance reviews over the previous year. It is easy to imagine the efficiency gain in turning rough notes into clean prose. It is equally easy to spend 30 minutes refining that prose rather than deciding what an employee actually needs to hear.

There is a similar risk at the line. Junior employees once learned by doing a lot of fairly tedious work badly, then less badly, then well. If the instinct becomes to hand that work to a model immediately, companies may save time before they have worked out how the judgment acquired through repetition gets replaced.

The useful dividing line is not whether new tech was used, it’s whether a tool actually gets work done better or faster. It seems painfully obvious, yet it we’re all seeming to forget it.

Hiring precision becomes critical as talent concentrates

The labor market can look crowded right up until a company tries to hire for the work it actually needs done. Routine tasks are easier to automate, outsource or teach than they were a few years ago, which puts more value on the harder combination of judgment, experience and context.

That helps explain why employers can receive hundreds of applications and still struggle to find a credible hire. Robert Half found 57% of U.S. hiring managers were offering above-plan pay, largely to secure specialized skills.

Part of the problem is that companies are often still hiring against roles that have drifted away from the work. Job descriptions are now frequently two to four years out of date. This makes a thin market feel thinner: employers screen for familiar titles, credentials and responsibilities while the qualities that actually matter may be much narrower.

A better approach is asking what someone must already know to be useful on day one, what can be learned, and what expertise can only brought in from outside.

Quote of the Week: Easy to say, hard to do

“We must never lose sight of what matters most: our people. We will build a culture where people feel respected, empowered, supported and proud of the work they do.”

—David Ellison and Ynon Kreiz, co-CEOs of the newly formed Skydance, in a joint memo to employees after the Warner Bros merger with Paramount

Reading List:

How can you support employee finances outside of raises?

Some of the cheapest financial benefits are the ones that help employees avoid unnecessary costs. Earned-wage access can prevent an overdraft, benefit navigation can uncover support people already have, and better guidance can reduce expensive mistakes. But employers should be wary of turning “financial wellbeing” into another fee-bearing product: according to the Consumer Financial Protection Bureau, around 90% of workers paid at least one fee when employers did not cover access. A benefit should leave employees with more money, not simply more ways to spend it.

“Calendar stalking” is becoming more common

Durable hybrid work is creating a new kind of office politics: employees are not just deciding when to come in, but when it is most useful to be seen coming in. Owl Labs found 48% had participated in or planned a “billboard day”, timing office attendance around leaders or clients. That is rational if proximity still influences recognition. The management problem is not the behavior itself, but the signal it sends about what employees think gets rewarded.

Deepfake scams hit more businesses

The old reassurance that “I saw them” is rapidly losing reliability. The FBI has warned about stolen identities and manipulated video in remote hiring, particularly for roles with access to sensitive systems. As synthetic media improves, more business processes will have to separate familiarity from verification. Hiring, payment changes and privileged access increasingly need a second channel precisely as faces and voices reach a point where not even mothers can tell the difference.

Data Point: So much for prompting

25%

The fall in demand for basic AI skills since January 2026, while more in-depth AI skills, like building tools, automating workflows, and AI engineering, has risen 51%

In Other News

• The biggest predictor of L&D success? How much time managers can spare. (HR Dive)

• The Full Monty: New York Employees Gain the Right to Examine Their Personnel Files, With Serious Implications for Employers. (Clark Hill)

• Fractional CHRO vs. Interim HR Leader: Key Differences and When to Hire Each. (HuntScanlon)

• Trump administration revamps insurer price transparency reporting. (HR Dive)

• McDonald’s hit with class action alleging AI-powered menu price-fixing. (Reuters)

• Gen Z can’t control the future, so they’re paying witches and tarot readers to make it feel more manageable. (Fortune)

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By Ken Stibler; Powered by Reyvism

Yes it's getting worse…so where is the middle ground on GenZ communications?

Every generation complains about how the next one talks. What’s different now is speed. With 15-to-24-year-olds averaging nearly four hours a day on social media alone, slang no longer moves through a school hallway over a few years. It moves through algorithms in weeks, and it splinters by platform, game and fandom along the way. Dictionary.com’s 2025 Word of the Year was “67,” a term the editors themselves called “meaningless, ubiquitous, and nonsensical.”

So this isn’t just hand-wringing. In a recent survey of U.S. workers, 80% of Gen Z said generational differences in workplace language were a challenge, against 30% of boomers. Three quarters of boomers had no idea what “delulu” meant.

More tellingly - and slightly comforting - 41% of Gen Z didn’t know what Gen Alpha’s “Ohio” meant either. The language is segmenting so quickly that even young people can’t keep up with each other, and Gen Alpha is already arriving: 23% of HR professionals report hiring Gen Alpha workers.

It cuts both ways. Only 22% of the same Gen Z workers knew exactly what it means to “boil the ocean.” Across offices, 68% of workers regularly hear phrases they don’t understand, and more than a third would be embarrassed to ask. That’s how instructions get misread and meetings go quiet.

We’ve already solved a version of this problem with dress codes. The share of companies enforcing strict dress codes fell from 30% in 2018 to 4.3% in 2024, but most didn’t drop standards altogether. They moved to “dress for your day”: casual on a team call, polished in front of a client, and a short list of things that are never okay. Nobody had to love khakis. They just had to know where the line was.

Communication deserves the same treatment: a low, clear, achievable bar, written down and explained. A one-page “communicate for your audience” standard could cover:

• Channels: what warrants a call (running late, a customer problem), what fits a text or Slack, and what has to be in email

• Timing: what “by Friday” or “ASAP” actually means, and expected response windows

• Audience: plain, complete sentences for customers and anything forwarded outside the team; internal chat can stay loose

• Both directions: managers drop the “blue-sky” jargon too, and anyone can ask what a term means without penalty

The point isn’t policing slang or learning (mercifully). It’s to make sure everyone can read the work. Language will keep changing faster than any policy, but common legibility is a reasonable thing to expect, as long as someone has the honest conversation about what it looks like.

Personal agentic AI raises an immediate volume problem for customer service orgs

“Agents” have moved from a software category into consumer behavior. Meta’s newly released Muse can complete forms, make calls, and negotiate on a user’s behalf.

And less than a month into availability, consumers are flooding social media with stories of agents sitting on hold, negotiating bills, cancelling subscriptions and seeking insurance preauthorization, while banks, insurers and outsourcers work out how to handle them.

This creates a fairly urgent problem for any service orgs. Bots are endlessly patient, will call five times to confirm one booking, and often fail authentication anyway, so the call eats agent time and goes nowhere. And with 74% of consumers saying they’d hand routine tasks like negotiating deals and resolving complaints to an agent, that volume is coming.

Most readers’ businesses have a bit of lead time, and it’s worth using it. Deciding which requests an agent can complete on someone’s behalf and which require the actual customer, giving frontline staff permission to end unproductive bot calls, and fixing QA scoring so people aren’t dinged for their “empathy” toward software (it’s already happening) can help blunt the wave of “why not” agentic outreach.

Quote of the Week: Silent signals

“It’s gotten harder and harder for employers to know who can actually do the job anymore.”

— Dan Shapero, LinkedIn CEO

Reading List:

The labor market is grinding to a halt

Layoffs are low, with September's 43,281 announced cuts the fewest for the month since 2022, but hiring plans were the weakest for September in fifteen years. Meanwhile the average job search has passed six months and nearly 2 million Americans are long-term unemployed, hitting experienced white-collar workers and new grads hardest. Low-fire, low-hire looks stable from the top and frozen from the inside. For those still hiring here’s an opportunity to outperform the algorithms as employment gaps become a lower value signal of whether someone can do the work.

Folding AI spending into employee cost?

Finance software firm Esker is including AI token consumption in employee cost planning, alongside salary, bonuses and payroll taxes, after spending roughly four times its AI budget. In one survey, 72% of finance leaders reported spending more than planned on AI, while 65% of CFOs struggled to connect usage with business outcomes. HR has a reason to join that discussion: the resources needed to do a role are changing and AI systems fit awkwardly within the tech function anyways.

Last in line for training, high performer disengagement rises

Should limited development dollars go to stars or to the people who need them most? A new study finds the answer depends on culture: in meritocratic workplaces, high performers felt slighted when passed over, while in more egalitarian ones it was lower performers. Managers who only weigh productivity can create a fairness problem they never see coming. Make the selection criteria explicit before you hand out the seat, and offer your high performers a different form of investment, like stretch assignments or exposure, rather than nothing.

Data Point: The entry-level still exists

57%

The share of U.S. workers in jobs requiring no prior work experience in 2025, according to the Bureau of Labor Statistics

In Other News

• The Surprises That New CEOs Face. (WSJ CEO Brief)

• AI skill levels drive workforce divide, PwC finds. (HR Dive)

• Skilled trades face worker shortage as industries recruit the next generation. (Scripps News)

• Ghost jobs and fake applicants have created a hiring trust gap. (HR Dive)

• AI could force 11 million US workers into new careers by 2035. (CNN)

• Technology isn’t yet solving HR’s workflow problems. (HR Dive)

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By Ken Stibler; Powered by Reyvism

Every job can’t be a senior job

Companies are trying to abandon the junior work and the workers that do it. Across millions of job posts, senior employment rose 6.7% over five years while junior employment fell 3%. The study records a broader but quieter workforce shift towards senior level-experience being the starting point for any new hire.

Yet while this “grayer” team of the future solves several common complaints with younger employees, there are real consequences when a company builds a workforce with all ceiling and no floor.

Flat looks efficient until a customer calls - rather than uses the portal - to say an order arrived short. Someone has to check the order, find the missing item, decide whether to expedite a replacement and call the customer back. On a balanced team, a newer account person handles most of the sequence and brings the costly exception to an experienced manager. On a flat team, the manager does all of it because nobody has seen enough cases.

In many cases, without removing broken or inefficient processes, senior time is swallowed by routine work, the customer waits longer and the next person still has not learned enough to own the next call.

While there’s an obvious cost in higher payroll, the hidden bill is service risk as a capable worker gets overwhelmed by volume or change

A generally useful question with current teams of all sizes is: what your most experienced people do all day? If they spent it on the calls nobody else could make, the company has the right mix. If they spent it moving orders, chasing information and cleaning up repeatable problems, experience has become an expensive substitute for a development system.

Judgement trumps skills in the new world of work

An employee can have every skill the job requires and still make the wrong call. A customer is angry, a shipment is late and there are two sensible ways to respond: make good immediately or protect the margin while the facts come in. The useful person knows what to ask, whose view is missing and which consequence carries more weight.

It’s critical, hard to train, and why Adam Grant has argued in a now-viral essay that the currency of success is shifting toward human judgment. Experience stays valuable. So do technical skills. But software, processes and research methods change quickly, while judgment tells a person which new fact changes the answer, when a routine case has become an exception and when somebody needs to escalate. That is increasingly the difference between a person who produces work and one who can carry responsibility for it.

Quote of the Week:

“Human judgment is going to supersede human expertise.”

—Adam Grant, a bestselling author and organizational psychologist, on how AI is changing the skills needed to perform white-collar roles

Reading List:

What do we actually want out of young people?

The most AI-exposed junior roles were 7 times more likely to demand skills previously associated with senior work than the least-exposed roles. A JD that asks a fresh hire to arrive with judgment the business has never taught moves cost from a training bill to a longer talent hunt. For the next junior role, separate what must be done safely on day one, what they can learn in year one and what still needs a manager’s call. The missing learning plan gets clear quickly.

Apprentice managers become popular as leadership benches thin

Chipotle has apprentices working toward management in about 75% of its restaurants and plans to place them in all locations by the end of 2027. They provide busy-period coverage and own training and digital operations as the chain opens 350 to 370 locations. Chipotle says restaurants with apprentices have higher operational scores, a company claim. The small-business lesson: choose a recurring decision that cannot wait for the manager, give a named person room to practice it and make the escalation rule obvious.

AI-generated content drowns L&D

AI has made it easier to produce learning material and harder to know what employees should trust. A new study of L&D experts found that nearly 40% saw managing and updating “content” as their biggest barrier to business value, more than twice the share naming content creation. Each course, job aid and policy needs an owner, review date and retirement plan. Let AI speed the draft; but make people accountable for accuracy, approval and the version employees can find. L&D’s scarce resource is content control.

Data Point: AI without the human quotient

46%

Share of organizations that do not bring in the CHRO to help define AI strategy

In Other News

• In the AI era, organizations must redesign work in real time, Gartner says. (HR Dive)

• AI is already deciding who gets hired and who gets rejected. Recruiting has no standard, no association writing one, and no agreement on where the lines are. (ERE)

• Older workers struggle to showcase their true skills on freelancing platforms, study says. (HR Dive)

• Amazon is trying to rehire workers it laid off, emails show. (Business Insider)

• Feeling Unmotivated at Work? You Might Be Experiencing “Rust Out” Instead of Burnout. (Real Simple)

• California’s AI-in-the-Workplace Legislative Blitz: California Legislature Passes Four New Bills That May Affect Employers. (National Law Review)

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By Ken Stibler; Powered by Reyvism

Skills shortages are here to stay. Here’s how you respond

Last week’s issue covered how talent shortages were already hitting companies’ growth plans, which kicked off several interesting conversations with subscribers about how deep the problem really ran. So this week we dove deeper into the demographic data (which has always felt like next decade’s problem) and saw that this condition looks more structural than cyclical. Between aging, immigration, and slowing population growth, the U.S. labor force is set to fall from now for the foreseeable future.

The headline numbers don’t tell the story as well as the loss of that individual contributor with decades of accumulated experience or the odd difficulty hiring for a role despite a down labor market. Most businesses I talk with are starting to have these gaps - and their associated eye-watering recruiting fees - become a regular low-grade headache.

Some of this is labor market efficiency degrading because of AI, as we have written about previously. But there’s another side to the problem: most employers narrow the pool using yesterday’s measuring stick long before they meet a candidate. A title, degree, and uninterrupted experience make screening faster, yet they often tell you less than the work itself.

For example, only 19% of people entering childcare roles came from childcare; people arrived from at least nine other occupations, including education, retail and food service. Nursing, on the other hand, has a more closed pipeline because training and licensing matter and, in turn, much sharper shortages.

Some requirements protect safety, but many others are habits masquerading as standards. Manufacturing has the same problem in another form: people leaving carry shop-floor knowledge that manuals rarely capture, and apprentices need years of supervised practice.

This is where HR starts being a critical strategic partner in the critical process of mapping the supply chain talent: which tasks require a license or deep experience, what are adjacent skills you can teach (because we can’t assume they’re purchasable anymore), what’s the time to build the competence, and who inside the organization can step up if given the support.

Once you understand the problem, invest while the work is still covered: apprenticeships, manager-led practice, knowledge transfer and an internal bench. Only four in 10 leaders say they are effectively building that bench and an AI license or untrained 20-something will not close this gap without serious support.

Most of us have had careers where every year there were more people buying more things and looking for more jobs. With the supply of both dwindling every year now, growth targets now need to answer who can do the work, and how will they learn it?

How big is the change cost for getting to “multi-agentic AI”

Companies are getting beyond chatbots in the hunt for AI-gains, increasingly looking to multi-agentic AI, or multiple AIs working together to complete tasks (as visualized below). This next class of AI promises to handle the work between functions: verifying information, reconciling constraints and routing routine decisions that consume an estimated 35% to 60% of back-office time, often without a clear owner.

Yet the cost of the change needed to pursue this this sits well outside the software budget. Eighty percent of organizations say AI has improved individual productivity, yet only 37% attribute any financial impact to it.

An agent cannot safely take over that work until someone has decided what the work is. In one manufacturer, the tech team had to spend four months sorting routine verification from constrained reconciliation and genuine exceptions before building the system. The same team has a lot more work that looks more like process design than coding: confidence thresholds, business rules, escalation paths and human accountability.

McKinsey analysis finds that roughly 70% of AI effort is in organizational redesign, rather than technology or model development.

For businesses that are ready for what’s beyond ChatGPT, start with a workflow where slow handoffs cost you money or customers. Measure the delay, then give one cross-functional owner responsibility for its data, decisions and exceptions. Begin with reporting and reconciliation, move to bounded actions once the data and audit trail are reliable. Skipping that time-intensive and slightly annoying redesign just gives you faster output with the same value bottlenecks.

Quote of the Week: Successful succession

“Too many succession conversations still begin with who is next in line, when the more important question is what leadership the future strategy will require. That shift changes the work.”

— Heather Foust-Cummings, co-author of the i4cp report on succession planning

Reading List:

How to channel employees’ frozen anger

Several surveys this week show Gen Z employees from manufacturing to healthcare (the few sectors actually hiring) reporting 70+ percent intent to quit within a year. Wanting to leave and landing a better role are different things, though, and there’s zero chance of that happening in this job market. Still, this frozen frustration needs an outlet. Give people closest to the work the autonomy to improve their jobs and customer experience while seeing their ideas go somewhere. Deputizing employees to fix the pointless steps, bad handoffs and customer irritants can be a free engagement boost rather than allowing frustration to become a quiet drain on engagement and performance.

Speed of change complicates more types of operations

The speed of change is creating operational confusion across hiring and security. More than half of 1,800-plus AI-labelled job postings bundled skills from at least two distinct roles. At the same time, AI-accelerated cyber risk is pushing teams to need more just to keep up even as overall security budgets rise only modestly. In a world where frenetic effort feels more affordable than any pause, clarity becomes key. The work is changing too quickly to outsource clarity to an AI, employee or vendor.

Minimum wage creeps up as major employers push higher

Amazon became the latest company to boost its minimum wage to $20 in what’s starting to look like the market pricing in a new minimum wage. The company raised pay by $1 an hour for eligible core-operations employees and paired it with grocery discounts and a financial-services benefit. That bundle matters as much as the headline rate when workers are deciding whether a job covers the cost of showing up as inflation erodes each paycheck. With many while-collar starting roles starting to be hourly-comparable to service jobs, it’s worth checking whether you’re paying for talent but buying “butts in seats.” Because your employees are certainly doing the math.

Data Point: Millions short

2.1 million

The number of manufacturing jobs could go unfilled in the U.S. by 2030 according to Deloitte and The Manufacturing Institute.

In Other News

• Great to hand to your people - the new rules for succeeding at work. (Wall Street Journal)

• Adjusting personality to fit in at work is a key skill, hiring managers say. (HR Dive)

• Record high waitlists for childcare assistance have shut women out of work and promotions. (19th the News)

• AI summaries leave a paper trail recruiters might not be ready for: “A job seeker’s mistake could be recorded permanently. An interviewer’s insensitive — or even illegal — question could also be captured,” one CEO said. (HR Dive)

• Your AI vendor could land you in legal hot water – what business experts say you must do. (ZDNET)

• HR must set boundaries as it embraces AI notetakers, experts caution. (HR Dive)

• Shopify CEO says employees’ ‘slop grenades’ are making more work for everyone else. (Fortune)

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By Ken Stibler; Powered by Reyvism

Leadership’s next challenge: saying no to AI madness

Every new AI announcement is starting to feel like a mini crisis. Whether global concerns or rushed conversations about what a competitor is doing, it’s easier than ever to feel always behind, and that immediate action is required.

This condition produces a lot of activity and very little judgment. Given that major change initiatives take more than three months to recover from on average, most leaders are planning around a disruption that shows no sign of ending anytime soon.

Saying no is how leaders give an organization room to think. The problem starts when every task becomes a candidate for automation and every new model triggers even low-grade changes.

While the change budget is being taxes, the real budget is being distorted. Customer-service organizations are among many already moving budget from people to technology: AI spending rose 38% while total service-and-support budgets grew 2%.

As just one anecdote of many such re-allocations, raiding the customer service budget leaves fewer people handling the cases where context, relationships or difficult judgment matter. When we’re moving money from revenue-centric activity to back-office tech, it’s a good bet that things have gone too far.

Leadership is pushing AI, and only leadership can set the boundary. Teams will keep saying yes when a new tool promises speed. Leadership has to decide which work needs a slower process: consequential people decisions, customer escalations, novel strategy questions and the coaching conversations where managers learn to make a call.

Give every deployment a business problem, a human owner, a quality measure and a date to reassess it. Stop the ones that create churn, rework or more supervision than value. Basic quality and competitive advantage may soon come down to the discipline to say no in a world rushing to remove human an equation that doesn’t work without it.

Talent issues throttle company growth while HR is collecting unfunded initiatives

A company cannot outgrow the people doing the work, yet many growth plans assume exactly that. 61% of employers expect revenue growth by 2027, while only half expect to add headcount. At the same time, 63% reported turnover of at least 10% last year. Every departure stretches the people left behind, slows decisions and puts more work on managers carrying adoption, performance and retention.

HR is handed the clean-up work. Retain people. Improve manager capability. Build trust around AI. Redesign performance. Collect feedback. More than half of employers have run an engagement survey since 2024 and still have not acted on it.

Meanwhile, 55% of HR leaders have considered leaving the profession in the past year, driven by feeling undervalued, operating in crisis mode and burnout. Before adding another priority, ask who owns it, what capacity they have, what will stop and which business result will move. If none of those answers exist, HR is collecting requests, not supporting a growth agenda.

Quote of the Week: New Job Descriptions

About 1% of US professional jobs are now “AI jobs,” i.e. jobs that wouldn’t otherwise exist without this technology. The share of AI jobs in computer and life sciences is estimated to be even higher, at 4–5%.

— Data from The Economist

Reading List:

Stock option compensation expands across

More rank-and-file employees are being asked to share the company’s upside and its risk. Sales employees receiving equity grants rose almost 30% since mid-2025, while marketing teams saw a 24% increase, according to Deel’s analysis of 8,000 grants. Equity can make a retention offer more meaningful. It also vests slowly, may be hard to sell and can lose value fast. Explain the strike price, vesting schedule, tax implications and downside in plain English. A stock grant earns trust when people understand what they received.

AI is creating some annoying colleagues

AI colleagues already have some familiar office habits: they need constant supervision, generate questionable work and attract a surprising amount of credit. Office workers are spending upward of six hours a week “botsitting”, providing context, checking output and fixing mistakes. The agent count has become a status metric, even though one person’s “20 agents” may mean 20 narrow automations that need daily maintenance. Ask a simpler question: did the agent remove a real bottleneck, improve quality or shorten a cycle time? If it did not, the digital org chart is just another source of busy work.

New layoff strategy targets expensive “micro-teams”

“Micro-teams” are creating a new spreadsheet target for layoffs, the WSJ reports. Uber plans to cut the number of managers with one or two direct reports by nearly half, part of a broader reduction that will leave it with 20% fewer managers. Google has already reduced managers of small teams by 35%. Some organizations need fewer layers, but small teams also give strong individual contributors a first chance to lead. Before flattening any chart, it’s worth mapping who handles the less visible work of coaching larger teams, where emerging managers will come from, and how employees will get time with a boss responsible for twice as many people.

Data Point: Cost of Change

41%

The share of organizations affected by an unexpectedly disruptive change that needed more than three months to recover according to learning and development company Insights

In Other News

• The trades need better training to spot other trades’ jobsite hazards. (Construction Dive)

• American Workers Have Slammed the Brakes on Switching Jobs: The country is adding around 80,000 jobs a month, up from last year, but workers are still wary. (Wall Street Journal)

• Data centers will create a fraction of the jobs the tech industry promised, think tank finds. (Quartz)

• How Meta tried, and failed, to grab its employees’ data for AI. (Business Insider)

• Japan eyes employing foreign trainees as airport ground crew: Tokyo aims to provide more long-term support for industry facing labor shortage. (Nikkei)

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By Ken Stibler; Powered by Reyvism

Personality is becoming more valuable than skills

Skills used to provide a reasonable building block and forecast for talent. If someone could do the work required by the job today, an employer could expect that skill to remain useful tomorrow. That is becoming a bad bet as new tools and workflow shifts move faster than job descriptions. A long list of skills tells you less and less about the contribution you are buying

Personality - long overlooked in favor of “harder” metrics - is stepping in to pick up some of that slack. Here, that means operating habits under uncertainty: curiosity, judgment, follow-through, candor about what someone does not know and the willingness to involve another person in a hard problem - 86% of hiring decision-makers say the right personality can outweigh a skills gap.

That changes what a strong interview looks like. A candidate who can describe yesterday’s toolset may help for a while. A candidate who can interrogate a clean-looking answer, revise a view when evidence changes and work through an unfamiliar customer problem gives you a better chance of staying useful as the role moves.

Test for it directly. Give candidates incomplete information, competing priorities or a real decision with no neat answer. Watch how they think, where they ask for help and whether they can explain the trade-off they made. Skills are still the price of entry. Personality increasingly determines the return on the hire.

August labor figures hide a rotting core

August’s 162,000-job report is being treated as the precursor for a hiring recovery, with HR publications warning employers will need to sharpen their pencils to get top talent. Trouble is, the stats are lying. The jobs added are almost all concentrated in a handful of sectors: restaurants, local government, education, and healthcare. Most other white-collar professions lost jobs.

One national unemployment rate blends workers competing for desk-based roles with workers employers need on site and tells you little about the scarcity of either. The result is bad decision-making: white-collar talent remains firmly a buyer’s market, while electricians, technicians, healthcare support and frontline service workers command faster decisions and higher budgets. Start every hiring plan with the market for that specific role (AI makes this cheap and easy to do so there’s no excuse) because the national number may create a fear of missing out that shouldn’t actually exist.

Quote of the Week: Rebranding Consulting

“Forward-deployed engineer sounds to many people a lot better than customer-based engineer.”

—Nick Bloom, a Stanford economist, on a nearly 730% increase in job postings for ‘forward-deployed engineer’ roles, which help customers integrate AI tools

Reading List:

Employees’ preferred benefits shift from wellness to cash

Employees have stopped treating wellness as a proxy for security. A Gartner survey of more than 10,000 employees found much stronger demand for spot bonuses and protection from unanticipated costs. This makes sense as healthcare costs rise, job security erodes, and inflation remains persistent. Wellness benefits, which became popular post-COVID, do not cover an unexpected medical bill. Lower deductibles, a steadier paycheck or help with a recurring cost will carry more weight than another broad wellness menu.

How long should a turnaround take?

Most turnarounds are likely getting judged against the wrong clock. Spencer Stuart’s CEO research finds that companies need about three years for a full reset. Year one is about a credible diagnosis, team and priorities; year two should show movement in retention, product momentum, market share and operations. Given that three years feels like an eternity in this climate, making sure strategy is sharp enough to avoid the need for turnarounds in the first place seems like an especially good investment.

Human-shaped hoops become foundational in post-AI hiring

We’ve talked multiple times about how old hiring evidence is now easy to fake. HR is pushing back, though, and a new set of best practices is emerging: shared documents, live assignments and in-person technical work are becoming foundational. A polished résumé, one-way video answer or take-home assignment no longer tells you much about how a person thinks. Ask candidates to reason through an unfamiliar problem, explain a past decision and respond when the facts change. You are looking for judgment and personality rather than polish.

Data Point: Overboard Onboarding?

60%

Share of onboarding materials employees found relevant, according to an Adobe survey. Adobe also found that employees receive an average of 13 onboarding documents and spend about 12 hours reviewing materials during their first week.

In Other News

• Williams-Sonoma to spread tariff refunds to vendors, employees. (HR Dive)

• Preparing workers for an uncertain AI future: As more businesses use the technology, Ninth District states are looking for ways to help with training. (Federal Reserve Bank of Minneapolis)

• Employers offer loan repayment, ‘re-recruiting’ to attract skilled labor. (Facilities Dive)

• Millennials Shared 19 Boomer Workplace Rules They Can’t Wait To Get Rid Of “My fun fact is” no more! (Buzzfeed)

• Colorado Unveils New Proposed Rules Implementing Revamped AI Act. (Ogletree Deakens)

• What’s the salary? These employers aren’t saying, despite warnings from New York regulators. (Business Insider)

• Why Kyndryl introduced a new AI role: We ask IT pros if the human systems architect role will gain traction within the industry. (IT Brew)

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By Ken Stibler; Powered by Reyvism

Companies are rushing back to human intelligence

Consultancy EY is putting $100 million into cash awards for adaptability, innovation and judgment. It is a not-so-small and very telling sign of a quiet rush back to human intelligence.

Knowledge work has always depended on the person who can build trust, ask the question nobody else asked, see trouble coming and take responsibility for a hard call. That work is suddenly easier to distinguish from routine output.

Professional-services firms are seeing it first, putting more junior people beside experienced colleagues because the work that once brought them together is disappearing. Remote work weakened that apprenticeship and automation can hollow it out further, leaving companies with polished employees who have never made a difficult call, fought a difficult client, or had to manage senior expectations on a project they didn’t fully understand.

Human intelligence is refined by opportunities to use it. AI may continue to absorb most HR conversations for the foreseeable future, but making sure you’ve got simple ways to nurture struggling juniors is a hedge against the artificial intel not working out as promised.

The Jevons paradox shows that when work gets more efficient we do more of the same work - it’ll be up to us as leaders not to use cleared admin work to generate more, and instead spend on nurturing and challenging the humans on our bench.

It's time to re-assess recruiting spend as job market effectiveness crumbles

The résumé has stopped being evidence as applicants can generate polished, tailored applications at industrial scale. One company in the space found that 58% of job seekers use AI (those are the ones that admitted it) and those users submit 41% more applications. Employers have answered with automated filters resulting in an arms race in which candidates send more convincing material and screening systems see less meaningful difference between it. Good people disappear beneath an avalanche of polished noise.

That makes high-volume recruiting an increasingly ineffective cost center. You pay to source applicants, pay software to sort them and ask recruiters to clear the residue, even as each pass tells you less about who can actually do the work. A keyword filter and one-way interview can reduce visible workload while hiding the candidate you needed.

The first screen increasingly now requires more care - and spending - timed work samples, referrals and live assessments work because they create evidence that cannot be mass-produced. This changes the economics of hiring in a way many firms haven’t fully thought through.

Without some magical (there are technical ways to do this with natural language processing, but it’s complex) way to identify the intersection of authentic resumes and component applications, you are paying to reject increasingly similar applications while the talent you want gets buried.

Quote of the Week: Pain in the Application

“It’s almost impossible to identify the signal from the noise.”

— Anthony Cheung, chief content and culture officer, AmplifyME

Reading List:

Managers cover confidence gaps with AI

A manager has a hard conversation on Friday and no idea how to prepare. The public chatbot is open, immediate and confident. The Predictive Index found that 72% see public AI tools as useful for this work, and 44% have entered employee names or performance information. 77% of frontline managers say their organization has not given them enough guidance for daily operational issues. This is a support failure with a privacy risk attached (especially as the usual states close in on tighter regulation). It’s worth giving managers a safe internal tool, conversation guides and direct support before a difficult case arrives.

Radical honesty is key to keeping up with rapid change

When the technology moves quickly, leaders feel pressure to sound settled before the facts are. That is how change gets magnified. A leader declares an AI direction, managers treat it as settled policy and teams start making choices around assumptions nobody has tested. Talogy found that 78% of talent leaders and practitioners struggle to assess AI skills, while only 38% feel very prepared to change job descriptions and career paths around AI. Say what is unclear. Ask the basic question. Name the decision that still needs evidence and invest in the learning to get it. That gives people a direction without pretending the answer is finished.

Remote work ROI shows why employees fight so hard not to return

A return-to-office mandate changes the compensation package, whether the pay stub changes or not. A recent study estimated that flexible arrangements added 56% to the effective value of pay through recovered time and avoided costs. The exact figure depends on assumptions. A commute still takes money, hours and attention; a separate survey found a one-third reduction in quit rates and no significant performance penalty over two years. Require office time where it improves mentoring, decisions or client work. Be ready to explain the return you expect from taking that value away.

Data Point:

44%

number managers surveyed had entered employee names or performance details into public AI tools while preparing for difficult conversations accord to data from Predictive Index

In Other News

• Nextdoor’s HR team halts people work once a month and dedicates the day to AI. (HR Brew)

• For young workers, the college advantage is breaking down. (Labor Matters)

• Only daily AI users feel positively about job security. (HR Dive)

• States Are Regulating AI Faster Than Washington—What Employers Must Know Now. (EBG Law)

• Employers at an ‘inflection point’ as health costs near double-digit increases: But many won’t be able to take drastic cost-cutting measures until 2028 at the earliest, the Business Group on Health’s president and CEO said. (HR Dive)

• AI-related growth edges out job cut fears in finance execs’ tech outlook: In an informal CFO Dive poll, 54% said they see AI’s biggest workforce impact being higher employee productivity. (HR Dive)

• AI-proof? Younger workers desert the digital world for traditional crafts. (The Guardian)

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By Ken Stibler; Powered by Reyvism

Why are over half of all workers planning to turn down promotions?

Your best individual contributors have started doing the math on management, and for an increasing number of them it doesn’t work. 59% of U.S. workers say they would turn down a promotion requiring availability outside normal hours, and 62% would reject a move into management if it cost them their boundaries, according to a survey cited by Fast Company. The title comes with a raise. It also comes with a second job: keeping an anxious team steady, translating decisions from above, handling harder conversations and remaining reachable after the workday ends.

Employees have increasingly developed this view of management just by watching what has happened over the last few years. 56% have seen colleagues become less happy after promotion. Layoffs, staffing gaps and AI adoption have loaded work into the middle of the organization, where managers deliver tighter targets and explain decisions they did not make. HR believes it has prepared them.

In a separate survey, 97% of HR professionals said their organizations provide adequate training for conversations around layoffs, AI anxiety and conflict. Only 41% of managers agreed. A prospective manager can see the deal from their desk.

That creates two workforce problems at once. Management has become a bad bargain for people who want to lead, while the default ladder still pushes high-performing specialists toward a role they may never have wanted.

The right, but difficult, path is to give technical, commercial and operational experts progression, status and pay without direct reports. Then rebuild the manager job around authority, capacity and a pay differential large enough to match the accountability. Gallup’s research shows that manager support shapes whether employees experience AI as an improvement or a threat. The people required to carry that work need a job worth accepting.

Financing costs set to put further pressure on raises, growth

Borrowing money just got more expensive. If you use a line of credit to carry inventory, a loan to buy equipment or operating cash to open a location, your budget is getting tighter. Bond markets have pushed up long-dated Treasury yields, and the Treasury Department’s $4 billion buyback program calmed markets for barely a day before another sell-off, according to Fortune. That shows up in the rate on the next loan, the cash required to cover the gap between paying suppliers and getting paid, and the number of bad months you can carry.

In such an environment raises become an investment choice alongside technology, capacity and growth. An AI system without people who can redesign the process around it is a capital expense. So is a manager role left open because the raise cannot justify the work.

Before the budget hardens, it’s worth making three lists: jobs that protect current revenue, roles that turn prior technology investment into operating results and positions where a departure creates a costly bottleneck. Fund those separately from the standard raise pool. Other work may call for development, re-allocation or automation. That is a harder conversation than a flat percentage increase. It is also a more honest response to a world where capital no longer comes cheaply.

Quote of the Week:

“Companies are looking at these new grads to be their future leaders, and they want a pipeline for the future.”

— Shawn VanDerziel, president and CEO of the National Association of Colleges and Employers

Reading List:

Later retirement ages are dangerous for leadership development

Retirement is becoming less predictable, which makes waiting for a vacancy a weak leadership-development strategy. 35% of workers have pushed back their planned retirement age in the past three years, and 14% expect to retire at 70 or later, according to a MyPerfectResume survey. Senior people may stay because they need the income or leave abruptly when finances or health change. Give high-potential people scope, pay and development milestones before a senior seat opens, or risk losing them to somewhere else without a waiting line

I’d get starting thinking about a worker reallocation plan

DTC blender company SharkNinja is building an AI tool to go from quarterly close to day-to-day financial analysis. Gathering sales data, calculating margins and compiling expenses are real jobs across thousands of companies. As AI removes thousands of work hours in these cases, leadership has to decide where the people who did it go next. Faster numbers only matter if there’s someone prepared to act on them.

Monitoring tools offer visibility, but can create distortion as employees game the system

Monitoring systems measure the behavior they reward. Calendar entries explain an offline meeting. Keyboard activity can be imitated. 48% of workers in a Visier survey admitted exaggerating their AI use. Once a dashboard tracks presence, activity or tool use, the job includes managing the dashboard. Use that data for coaching questions and operational diagnostics, but performance judgments should be tied above all to customer outcomes, quality, decisions and work managers can directly observe

Data Point:

34%

The number of C-suite executives who say it is consistently clear who owns AI decision-making according to a survey by Pearl Meyer.

In Other News

• Zynga founder Mark Pincus: AI can get you to a B-plus, but it won’t get you to an A. (Fortune)

• ‘Did they ghost you?’ Website takes aim at employers who go radio silent on candidates: The site gives workers another platform to air out their grievances about employers. (HR Brew)

• CHROs more cautious about AI readiness and adoption than C-suite peers, survey finds. (HR Brew)

• Skilled labor demand is exploding. AI may be both a cause and a solution. (HR Dive)

• AI efforts drive up demand for analytics, database architecture skills. (CIO Dive)

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By Ken Stibler; Powered by Reyvism

How long do businesses have before labor weakness becomes a growth issue?

A weak labor market becomes a growth problem long before unemployment gets high. Payrolls fell by 23,000 in July, and May and June were revised down by 103,000. The unemployment rate still dropped to 4.1%, largely because people exited the labor force.

At the same time, small-business optimism reached an 11-month high, with one in five owners planning to hire and one in four planning capital spending. The quiet part out loud: those growth plans depend on customers feeling secure enough to spend, and the labor market is giving them fewer reasons to do so.

The pressure goes beyond a weak jobs report. More than half of workers say leaders live in a different world. Nearly one-third of CEOs say reducing headcount is the primary reason for AI investment, while almost half of employees report little or no employer-sponsored AI training.

A person who sees layoffs around them, watches their employer automate work and cannot see a path to their next role behaves differently as a customer. They delay purchases, trade down and hold cash. That spreads through the economy at different speeds: directly to consumer businesses, then to the manufacturers, service providers and suppliers behind them.

The response is more specific than a broad growth plan. Start by identifying where your revenue actually depends on discretionary demand and where customers are exposed to job insecurity. Then test those markets for real purchasing power, local hiring, order velocity and/or payment behavior.

Inflation-adjusted local income data is useful because headline GDP and retail-sales figures can hide flat demand. Shift sales coverage and growth investment toward the customers and geographies still expanding. Labor weakness is already a sales concern. Seeing it early preserves the ability to choose where to grow.

Engaging workers that are ‘coming in from the cold’

68,000 people came to a Texas job fair last week for roughly 670 employers. One recent graduate had been looking for six months without a single interview.

Another candidate said AI had scanned his resume, decided he was not good enough and ensured that no human saw it. People hired out of this market will arrive with a view of work shaped by months, sometimes years, of rejection, opaque systems and silence. They will not walk through the door with the trust of a normal new hire.

That makes engagement part of the hiring job. A welcome package and an orientation deck will not do much for someone who has learned that employers say one thing and do another. In the first month, show them the work they own, the decisions they can make, how performance is measured and where the role can lead.

Answer questions before they have time to become suspicions. More than half of employees already say their leaders live in a different world, and 72% say leadership made at least one decision last year that made no sense to them. A new hire needs evidence that the role is real and the person managing it has time for them. Engagement begins with proving you meant it when you hired them.

Quote of the Week:

“We are simply witnessing a historic exit from the American labor market.”

— Joe Brusuelas, Chief Economist, RSM US

Reading List:

Manager skill gaps create a weak link

Senior executives may be the only layer that believes managers are ready. Two-thirds of executive-level people managers say they feel very prepared for today’s leadership challenges. Only 42% of senior and middle managers agree. Just 35% of managers say AI has made their job significantly easier; many report more employee anxiety and pressure to deliver with fewer resources. Every strategy on AI, career paths and organizational change reaches employees through this layer. If managers lack the skills for difficult conversations, new tools and shifting expectations, the weak link sits between the executive team and the workforce.

Job postings as competitive intel

Your competitor’s job posts may tell you more about next year’s strategy than its earnings call. Amazon began advertising satellite-engineering roles months before announcing Project Kuiper. Apple’s cluster of motion-science and optical-engineering openings pointed toward augmented reality well before it disclosed a product. The signal is in a pattern, not a single listing: recurring roles, changing seniority, new locations and unfamiliar technical requirements. Give someone on your team a monthly responsibility to track those patterns across your closest competitors. They are hiring for the future before they announce it.

Merging cultures is an increasingly valuable skill as every org is forced to change

Every organization is becoming a culture merger. Rocket Companies CEO Varun Krishna has spent three years blending Silicon Valley talent with Detroit grit, then took that work into $16 billion of acquisitions and an alliance with Compass. Half his leadership team came from Seattle, San Francisco, New York and Boston. His point is not that one culture wins. Loyalty, tenacity and institutional knowledge have value. So do outside perspective, speed and technical range. The work for leaders is deciding which habits to protect, which to retire and how to bring in new people without treating the people who built the business as the problem.

Data Point:

36%

Number of small-business owners that say they have positions sitting vacant, the highest share since June 2025, according to the National Federation of Independent Business

In Other News

• Stop Doing Low-Value Work. (Harvard Business Review)

• AI may be helping employees prepare for career mobility: Workers say they are using artificial intelligence to seek out development opportunities within their existing roles as well as outside their organizations. (HR Dive)

• Entry-Level Jobs Require More Specialized Skills as AI Automates Tasks: AI know-how is one way fresh college graduates can stand out, study finds. (Bloomberg)

• Saying ‘please’ or ‘ASAP’ may actually slow work down. (HR Dive)

• 14 Ways To Create An Onboarding Experience Employees Want To Stay For. (Forbes)

• Employment Law Is Becoming The Law Of Information. (Forbes)

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By Ken Stibler; Powered by Reyvism

Invest in your leadership pipeline before the river runs dry

Boards are calling retired CEOs back to work en-masse. Verizon, Boeing, and Cracker Barrel all tapped former executives who had already hung it up to fill their corner offices.

In the first half of 2026, 34% of CEOs appointed by S&P 500 companies previously led a public company, up from 22% a year prior. External hires are up from 18% to 33%. The supply chain for executive leadership is breaking down, and companies are reaching into the past because they didn’t build for the future.

The breakdown starts in the middle. Roughly a quarter of white-collar professionals hit a wall in their careers before their peak earning years, going at least five years without a real boost in pay or position. High-achieving corporate professionals are paying $4,000 for existential midlife retreats to process burnout, disillusionment, and the feeling that they are stuck in toxic environments where good ideas go to die. The people you need to run your organization in five years are currently stalled, exhausted, or looking for an exit.

If leadership is a supply chain, then most organizations have been running it just-in-time for decades, assuming the talent would be there when they needed it. Increasingly though, it isn’t there.

When this for-granted pipeline runs dry, the fix is expensive and usually involves bringing in outsiders who don’t know the culture or retirees who are kicking the can down the road. The time to invest in the people who will run your business is before you are desperate for them. Engagement efforts, mentorship, and ongoing training are known best practices, and while their expense can feel tough to justify quarter by quarter (spending is falling on all non-AI categories), its a lot cheaper than over-paying for outside talent.

Job market numbers are getting wacky

Labor market math just changed. The economy lost 23,000 jobs in July, defying estimates of an 85,000 gain. Something this bad used to signal a recession, yet the unemployment rate actually fell to 4.1%.

The seemingly contradictory (and slightly nerdy) numbers focuses masks a real people ops problem - the labor pool is rapidly shrinking. For years, the economy needed 125,000 to 150,000 new jobs a month just to keep unemployment steady and accommodate new entrants. Oxford Economics estimates that breakeven rate is now around 50,000.

Between restrictive immigration policies slashing the supply of foreign-born labor and the baby boomer retirement tsunami peaking over the next three years, that breakeven rate is heading to zero next year. It will turn negative in 2028. You can have a shrinking number of employed people and a stable unemployment rate at the same time.

For business planners trying to staff up, this is the reality check. The labor shortage is now structural, and the workers needed are not likely waiting on the sidelines for the economy to recover. They are retiring, or they are not entering the country. If you are holding out for the labor market to loosen up and make hiring easy again, you are waiting for a demographic reality that no longer exists.

Quote of the Week: Understanding before Decision

"The best leaders I've worked with do something different. They ask questions. They listen. They seek to understand before they decide."

— Mike Wirth, CEO, Chevron

Reading List:

Companies move away from standard raises towards more performance-based compensation

The era of the automatic 3% raise appears to be ending. In 2026, only 36% of U.S. organizations gave across-the-board pay increases. Only 32% plan to do it in 2027, according to Payscale’s Annual Salary Budget Survey. Those “peanut butter raises” (so named because the budget is spread evenly across the org) are actively demotivating high performers. With a quarter of firms losing employees last year due to insufficient pay increases. it seems that merit-based pay will de-facto become the norm even outside of sales.

Why you should lead like Ted Lasso

Last week we looked at why leading like Ted Lasso can backfire, when excessive optimism becomes denial and kindness becomes an inability to make hard calls. Lasso's appeal still rests on a genuine leadership discipline. One specific scene that’s a leadership classic to me is where Lasso playing darts, repeating the quote "be curious, not judgmental." It's easy to assume we already know the answer. but the best leaders ask questions and listen before deciding. Arizona State professor Christopher Neck makes the broader case for “Lasso leadership”: investing in people creates belief, and belief produces business results. Curiosity and kindness can work well, just as long as they come with standards, judgment and the willingness to take difficult actions.

Employees turn to AI-generated salary ranges, here's how to respond

Your employees are bringing ChatGPT-generated salary ranges into compensation talks and treating them like truth. The tool can’t see your internal equity, role scope or budget: an employee may see $95,000 for a role the business/market/niche can only support at $82,000. Rather than dismiss the number out of hand, these AI ranges can be an opportunity to explain how your organization makes pay decisions, how the role is calibrated, what the budget supports and where the employee can grow.

Data Point: Going back to the well

34%

Number of CEOs appointed by S&P 500 companies in the first half of 2026 previously led a public company, up from 22% the year prior according to Russell Reynolds Associates.

In Other News

• Who needs consultants in the age of AI? Getting a company to implement recommended changes is a contact sport that only humans can play. (Financial Times)

• Can America retrain workers before AI leaves them behind? Success will require investing in employees as seriously as America invests in chips. (The Economist)

• Every company has an AI strategy. Very few have a human strategy. (AdaRose)

• Return-to-office mandates are killing workplace trust. (The Hill)

• Gen X employees say they are burned out from caregiving responsibilities. (HR Dive)

• Does outplacement need a makeover? Enter ‘outskilling’. (HR Brew)

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By Ken Stibler; Powered by Reyvism

What to do when the world is moving faster than your strategy

Most leaders are running 2026 organizations on 2024 assumptions. IBM’s CEO said as much when explaining his company’s 25% single day stock market collapse, to the Wall Street Journal this week. His assessment? The culture was too slow to change, the mindset still tied to massive licensing deals from a previous era.

This fear - and sometimes its real effects - are increasingly showing up in the C-Suite. ManpowerGroup surveyed 80 C-suite and senior talent leaders and found that only 3% are highly prepared to lead AI-enabled teams. Only 17% of organizations claim advanced workforce readiness. AI adoption keeps climbing. Employee engagement hasn’t moved. The tools showed up. The thinking didn’t.

The instinct when the world outruns your strategy is to build a new one. That won’t work if the assumptions underneath it haven’t changed. The better first move is personal: update your own mindset and resource allocation before you update the plan. Where are you spending your time? What are you reading? Who are you talking to? If the answers are the same as eighteen months ago, the new strategy will look a lot like the old one.

The redesign starts with how you organize your own attention. Block time this week to understand how AI is actually being used in your organization (or could). Talk to the people doing the work. You’ll find gaps between what was deployed and what is producing value. Those gaps are where your strategy needs to catch up. Trust me, you’ll feel better once you start.

Avoiding offloading talent to AI

Increasing amounts of the hiring market are becoming one person’s AI interacting with another’s. AI-generated resumes get screened by AI parsers. AI-written job posts attract AI-optimized applications. And the automation creep extends well beyond sourcing: 59% of managers now use AI when deciding who to lay off, 31% direct it to weigh sick days, 14% ask it to consider age, and nearly half of workers say they’d let AI negotiate their pay. Both sides are offloading the people decisions that matter most. The system is converging toward sameness.

This is happening while most organizations haven’t even equipped their people to use AI well. The Conference Board found that training still focuses on basic prompting, not advanced skills like managing AI agents. Only 14% of employees call themselves AI natives. Only one in three has done any employer-provided training in the past six months.

Strategically diverging from what is easy (putting human judgment back at the decision points that actually matter) is very quickly going to be the only way to differentiate when everyone else is defaulting to the machine.

Quote of the Week: Targeted re-design, not abstract change

“The ability to redesign how work is organized may become a more important determinant of success than technology deployment alone.”

— Sailesh Hota at Everest Group

Reading List:

Maybe don’t record that zoom call

AI tools are recording almost every work meeting and social interaction now. Slim mics, wearables, notetaking apps that join calls uninvited. Eleven states require all-party consent to record conversations. Lawyers in turn are calling it a "ticking time bomb of legal risk" where every offhand comment becomes potentially discoverable. People are adding "I do not consent to transcribing or recording" to their Zoom display names. If your people are using AI notetakers and you don't have a policy governing it, you have an unmanaged legal exposure that grows every week.

Should you lead like Ted Lasso?

Ted Lasso is charismatic, empathetic, and beloved, increasingly a mascot of optimistic leaders in the hit eponymous TV show about an American coaching soccer. While Ted can offer some great lessons, he also ignores defeat, overpromotes based on belief rather than evidence, rebukes help, and never learns from his mistakes. Research in Current Directions in Psychological Science confirms what the show illustrates: good traits done to excess can backfire, optimism without accountability can be denial, and kindness without standards eventually become an inability to make hard calls. The leadership qualities you think are your greatest strengths may be the ones creating your biggest blind spots.

Big companies re-accelerate hiring

America's biggest companies are finding they might need more people after all. After a year of holding back, companies from CSX to Google have told investors they plan to hire to meet growth goals. The reason matters: executives are saying the costs and limitations of AI demand more people, not fewer. If you cut headcount during the pause and your competitors didn't, the re-acceleration is going to be expensive.

Data Point: Not a lot of confidence

3%

Number of leaders that feel highly prepared to lead AI-enabled teams according to ManpowerGroup/Everest Group.

In Other News

• It’s still a tight job market, despite record-low initial unemployment claims: Initial claims for unemployment insurance fell to the lowest level since 1969 — but there are disturbing trends below the surface. (Marketplace)

• AI is coming for job titles. Here’s what HR needs to know: The majority (63%) of AI-related job titles are in non-tech industries. (HR Brew)

• AI Risk Disclosures Dominate Investor Filings This Year. (WSJ Risk and Compliance)

• Setting limits on employee AI use: An inside look at how to establish AI spending guardrails without stifling innovation. (CFO Brew)

• Confidence in HR may hinge on moving beyond task-level AI use. (HR Dive)

• Nearly a third of workers admit to sabotaging their company’s AI—and smaller paychecks may explain why. (Fortune)

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By Ken Stibler; Powered by Reyvism

Don’t try to “engage,” declare war on the hated parts of work

People don't hate working, they hate the specific conditions that increasingly make modern work feel uncomfortable. And when you look past the surface of growing “anti-work” movements like Financial Independence, Retire Early (FIRE), the motivation is rarely a desire to sit on a beach. It's a desire to escape the inability to speak honestly, the lack of control over one's own time, and the feeling that employment is a coin flip someone else is making.

The thousands of Google workers petitioning for layoff protections amid record AI investment are expressing the exact same impulse. One group is building an exit; the other is demanding the floor stop moving. Both are reacting to a work environment where volatility and uncertainty feel like permanent features.

Organizations have spent decades trying to "engage" employees by adding things (wellness apps, recognition platforms, culture initiatives). The data consistently shows this doesn't work at scale. What works is removing the things people hate.

A durable post-covid boom in entrepreneurship is evidence that talent will vote with its feet to find clarity over ambiguity, honest communication over corporate euphemism, and predictability where predictability is possible. They aren't leaving because they hate the work. They're leaving because they hate working under conditions they can't influence.

Declaring war on the hated parts of work is a competitive strategy, and the irritants aren't minor splinters. Left unaddressed, they compound into disengagement, attrition, and cultural rot. Organizations that remove ambiguity, create honest feedback loops, and give people genuine control over how they spend their time are doing more than fixing a culture problem. They're building the foundations of durable organizational and talent competitiveness.

A glimpse at HR’s strategic future

Project management software compare Atlassian just hired a Head of Human-AI Collaboration. The title sounds like a novelty, but the mandate is the future of the HR function: deciding what the machines should do and what the humans should do.

The Society for Human Resource Management is already pushing HR professionals to be come skills strategists” who align learning directly to business priorities, while defense agencies are shifting from job descriptions to skills intelligence to map human capability against automated capacity.

The risk of getting this boundary wrong is high. When organizations automate the wrong things, they invite cognitive surrender (the erosion of human judgment as people defer to the machine). They also break the apprenticeship model.

If AI does all the junior work, who mentors the junior staff? Figuring out how to integrate AI without destroying the talent pipeline is the advantage. It’s a massive one. HR is positioned to own this architectural work, but only if it claims the territory.

Quote of the Week: Demanding Layoff Protection

“These layoffs and cuts are not difficult decisions, but simply profit being put over the people that make this company run.”

—a petition from 4,500 Google employees to CEO Sundar Pichai, requesting layoff protections as AI threatens jobs

Reading List:

Overwhelmed CEOs increasingly to turn Chiefs of Staff

The complexity of the CEO role has outgrown one person's capacity. The rise of the $400,000 Chief of Staff is an admission that the job has become too large and too fast to run without a second brain. The role functions as a confidante and consigliere, giving a CEO breathing space by amplifying their vision and spearheading strategic projects. If your CEO is overwhelmed and you haven't discussed this role, you're behind.

Do you have an executive onboarding plan?

Most organizations have detailed onboarding for individual contributors and almost nothing for executives. The failure rate of external executive hires is directly attributable to this gap. A great executive onboarding plan requires structured integration: a 90-day plan, stakeholder mapping, and explicit cultural translation. If you're spending six figures on a search and then leaving the new hire to figure the culture out alone, you're wasting the investment.

Deepfakes overwhelm HR’s ability to tell fantastic from fake

AI-generated evidence is already arriving in HR inboxes. Fake doctor's notes, fabricated harassment claims, and synthetic video are overwhelming the verification systems most organizations rely on. Your investigation processes were designed for a world where documents were either real or obviously forged. But that world is gone. If your HR team doesn't have a verification protocol for digital evidence, you're exposed.

Data Point:

47%

The number of workers polled by Gallup who say their organization has adopted AI tools, up from 41% last quarter.

In Other News

• The Real Difference in the AI Era: Vision has to come from the top. (WSJ CEO Brief)

• The fallacy of the safe role: Why your career security is an inside job. (HR Executive)

• Burger King reworks manager role to support guest experience. (Restaurant Dive)

• Training AI models might be the chance for a workplace power play: It is becoming clear that the knowledge they require is currently locked inside employees’ heads. (Financial Times)

• Front-line workers say they don’t mind AI but want transparency. (HR Dive)

• Step Into the ‘Zone of Genius’ (Before A.I. Takes Your Job): A decades-old self-help concept is gaining new purchase among people searching for meaningful work in the age of artificial intelligence. (NYT)

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By Ken Stibler; Powered by Reyvism

Ensuring organizational sanity as AI "eats everything"

The initial promise of AI was frictionless efficiency. The reality is that organizations are paying massive software bills to watch their employees spend 6.4 hours a week “botsitting” automated output. Heavy AI users are submitting work they do not understand, generating “workslop” that degrades performance, and forcing managers to spend their time verifying rather than directing.

Yet more than half of CEOs still fear they are underinvesting in the technology. The pressure to adopt is so intense that companies are mobilizing internal AI superfans out of work and in to converting skeptics, treating hesitation as a culture problem.

This kind of pressure creates a trap for HR leaders. If you try to slow down unstrategic adoption, you look like a wet blanket standing in the way of progress. The way out is to claim the mantle of sanity. That means insisting that AI projects face a true assessment of return on investment. It means measuring the actual organizational costs of adoption: the engagement toll of botsitting, the time lost to verifying slop, and the hard costs of the licenses.

When Zuckerberg admits Meta’s AI restructuring is struggling despite hundreds of billions of dollars, it is a signal that the deployment-at-all-costs phase is ending (or at least should). The next phase belongs to organizations that treat AI as a capital allocation decision, not a religious movement. If you are the leader demanding that discipline, you are not slowing the company down. You are keeping it sane.

At this point, who is the job market working for?

It increasingly seems like the hiring market is broken for everyone simultaneously. Recruiters are drowning in fraud. By 2028, Gartner expects one in four candidate profiles to be fake. Thirteen percent of applicants admit to using chatbots live during interviews, and the take-home assessment pass rate at startups has jumped from 25% to 80% because candidates are automating the tests. The result is a surge in “regrettable hires” and a retreat to defensive tactics. Target, Google, and L’Oreal are now requiring in-person or AI-free interview rounds just to verify that the person on the screen is the person who will show up to work.

Job seekers are equally miserable. Ninety-five percent have encountered suspicious job offers, and nearly half are skeptical of all recruiter outreach. They are wading through a gauntlet of scams while competing against automated applicants for a shrinking pool of entry-level roles.

This friction is happening exactly when the economy can least afford it. The United States is facing a projected shortage of 4.6 million to 6 million workers as baby boomers retire and immigration slows. The semiconductor industry alone will be short 67,000 technicians and engineers by 2030. We are entering a period of historic labor scarcity with a matching engine that neither side trusts. If your hiring strategy relies on inbound volume and remote screening, you are optimizing for fraud. The advantage belongs to organizations that rebuild high-trust, high-friction sourcing channels before the shortage peaks.

Quote of the Week:

We knew it was coming. It’s kind of like standing on a beach watching a tsunami headed toward you and not being able to flee.”

—Rachel Bernier-Green, a small business owner, on having to drop healthcare coverage for her six employees due to rising costs

Reading List:

Workers use once-obscure law to take more mental health protection

One in six organizations saw a 25% jump in mental health leave over the past year. Workers are increasingly using the Family and Medical Leave Act to step away from burnout, anxiety, and depression. The cost of missed workdays now totals $47.6 billion annually in lost productivity. Companies expanded wellness benefits during the pandemic to reduce stigma, and it worked. Now, as organizations run leaner and demand more output, those expanded policies are creating operational strain.

Learning debt rises as education loses effectiveness

Forty-one percent of employees say their roles are evolving faster than their company can train them. To cope, six in ten are using AI to complete tasks they were never trained to do. That creates "learning debt": a growing backlog of unacquired skills masked by automated output. The debt comes due when the work requires judgment. The fix is program design. InStride data shows that 62% of top-performing education programs require no HR approval to enroll. They remove friction, tie directly to business priorities, and measure success by retention and capability. If your training program is hard to access, your employees will skip it and ask a chatbot instead.

Moving HR from compliance to coaching

Human resources professionals need to operate as coaches. Executive coaches argues that this transition requires establishing relationships before offering correction. If an employee only hears from HR when they are out of bounds, they will view the interaction as punitive. If the relationship exists first, the feedback becomes coaching. In remote environments, this means scheduling regular check-ins and observing behavior on video calls rather than waiting for a formal complaint. A coach is a vehicle that takes people from where they are to where they want to be. If your HR team is only managing risk, they are leaving performance on the table.

Data Point:

300%

Increase in job postings mentioning AI since 2022.

In Other News

• The Company Founder Who Got Fired for Ignoring His Own Return-to-Office Rules: A former executive alleges his fellow co-owners used the policy as an excuse to push him out of the asset-management firm he helped run. (Wall Street Journal)

• Great Leaders Know Which Emotions Their Feedback Will Trigger. (Harvard Business Review)

• Faith in higher ed slips: 38% of adults report high confidence. (Higher Education Dive)

• Tech used to be a mecca for young talent—now, AI start-ups are hiring fewer entry-level talent in favor of older workers with top degrees. (Fortune)

• Lower-skilled workers could earn more in an AI world, research indicates. (Phys.org)

• The hidden cost of empathy at work: White-collar women spend a full workday a week as their coworkers’ therapist. (Business Insider)

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By Ken Stibler; Powered by Reyvism

There's a lot of great talent on the market, it takes real systems to access

There are more skilled, recently displaced workers available right now than at any point since the pandemic recovery. The technology sector alone has shed 139,156 jobs through June, up 83% year over year, and AI has been cited in nearly a quarter of all cuts across industries. June payrolls came in at 57,000, well below projections, with the prior two months revised down by 74,000. The talent pool is deep. Most organizations cannot access it because their hiring systems were built for a different market.

The post-pandemic labor market was extraordinarily dynamic. Hiring surged, quits hit unprecedented levels, and workers moved aggressively toward better matches. That dynamism is what made the market healthy -- churn is how workers find higher wages, how firms find better talent, and how the economy reallocates people toward productivity.

What economists are now calling “slack water” is the opposite. Hiring is subdued, separations are scarce, and the matching process has frozen. The unemployment rate sits at 4.2% and looks fine. Underneath, the market is going sclerotic. A worker who would have changed jobs for a raise stays put. A firm that would have taken a chance on someone new holds off. Opportunities stop materializing.

That is a problem for the economy. For you, it is an opportunity…if you have the systems to act on it. In a frozen market, the best people are not applying. They are sitting tight, waiting. Reaching them requires outbound sourcing, referral infrastructure, and speed. If you built those systems during the tight years, you still have them. If you relied on inbound volume and job boards, you are staring at a pool of exceptional people with no way to reach them. The window will close when hiring picks back up and those people land somewhere else. Right now, it is open.

Soft skills are hard and hard skills are soft?

The skills that are hardest to hire for, most expensive to develop, and most resistant to automation are all “soft.” The skills that are easiest to learn, cheapest to source, and most vulnerable to automation are all “hard.” The conventional hierarchy has inverted. Software engineers are finding that the bottleneck with AI coding tools is cognitive, not technical.

The transition from writing code to reviewing and directing it requires ego management, intentional skepticism, and precise communication. Without those skills, developers waste hours rewriting functional automated output to match their personal style, or worse, blindly accept code that introduces technical debt.

Ford figured this out the expensive way. After recalls cost the automaker $4.8 billion per year, the company hired 350 veteran engineers specifically for their judgment and mentorship. They run mandatory peer design reviews to hunt for failure points before blueprints reach the factory floor, and they reprogram ineffective AI tools. The result is a jump from 10th to 1st in the JD Power Initial Quality Survey. The company attributes the turnaround to a culture change emphasizing the role of human workers.

Most organizations’ hiring criteria, compensation structures, and development budgets have not caught up to this inversion. They are still screening for syntax and syntax is now a commodity. If your hiring criteria, compensation structure, and development budget still prioritize technical skills over judgment and adaptability, they are optimized for a world that no longer exists.

Quote of the Week:

“The differentiators that turned AI into real performance included discernment, curiosity, connection and humility. Smart companies will ultimately shift to measuring how employees execute strong judgement in AI usage, instead of usage or tokens alone.”

— Leslie Caputo, organizational psychologist and SVP of global solutions at coaching platform EZRA

Reading List:

Interesting work drives engagement, can "interesting" be a part of every job?

Controlling for pay and benefits, workers who found their new job more interesting than their last one were 27% more likely to rate it better overall. Better work-life balance made them 18% more likely to prefer the new role. This data from the Bureau of Labor Statistics arrives as Gallup estimates 8 million people have disengaged at work since 2020. If you are losing people and your compensation is competitive, the problem may be that the work itself is boring. If AI is automating the interesting parts of a role while leaving the tedious oversight, you are making this worse.

Jobs are "senioritizating"

Entry-level AI-exposed roles are now seven times more likely to require skills traditionally associated with senior employees, including judgment, leadership, and face-to-face persuasion. Job openings for these newly elevated roles grew 35% since 2019, while traditional entry-level openings shrank 10%. The routine coordination and documentation work that once helped new employees build context is now handled by software. The consequence is that the first rung of the career ladder is structurally disappearing. If you are not deliberately building the judgment layer into early-career roles, you are contributing to a structural problem that will embedded in your org chart in five years.

Getting specific about where AI shouldn't be used in people

Managers are using chatbots to write performance reviews, draft PIPs, and decide who to promote. One sales strategist described her boss consulting ChatGPT like a "Bible," generating constant strategic pivots, monitoring Slack messages for tone, and overriding her judgment with the model's output. The pattern is consistent: the manager already has a decision and uses the tool to validate it. That is corrosive in a specific way. It removes the friction that forces a manager to defend a personnel decision to themselves before making it. If you are tracking AI use in performance reviews, you are measuring the wrong thing. Volume of AI use tells you nothing. Judgment in AI use tells you everything.

Data Point: Feeling the Squeeze

52%

Percentage of US workers are planning staycations this summer as costs rise.

In Other News

• CEO of $248 billion cybersecurity company says workers are about to face a ‘Darwinian moment’ thanks to AI: Evolve or get cut. (Fortune)

• Remote Work Is Making It Harder for Grads to Find (and Keep) Jobs: New research argues that frustration among employers over remote work may be leading them to cut back on hiring young workers. (Wall Street Journal)

• Early career workers’ wages can’t match inflation, Glassdoor finds. (HR Dive)

• White-collar America is having a nervous breakdown about AI: “For the first time in at least a generation,” an economist said, “the future is up for grabs, and they might not end up on top”. (Quartz)

• Gartner Says CHROs Must Identify Hidden Workforce Costs to Protect AI ROI. (Gartner)

• The diminishing political returns of a solid labor market. (Morning Money)

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By Ken Stibler; Powered by Reyvism

Change as a skill

Thirty-nine percent of core skills will change by 2030, according to the World Bank. MBA programs are rebuilding curricula around judgment as everything else becomes a commodity. And employers want AI proficiency from new hires…while complaining that Gen Z workers lack the critical thinking to use those tools well (more on that In Other News). Everyone agrees: build new skills. Yet skill (re)development is the right answer to the wrong question.

The harder question is whether your organization can keep building skills indefinitely without the building process itself becoming destabilizing. Reskilling programs have a target. They close a specific gap at a specific moment. What most organizations lack has no target: the ability to keep working while the next requirement is still forming. Call it change tolerance. A leadership discipline, not a training program.

In practice this looks like clear directions from January feeling abstract and inapplicable by February. A major initiative gets reprioritized, two experienced people rotate out, their replacements arrive with different assumptions. Each shift is manageable alone. In combination, they erode alignment faster than leaders can restore it.

No reskilling budget touches that problem. What touches it is whether your managers have the mandate to rebuild shared understanding every time the context moves and whether they have the time. Right now almost none do.

AI is increasingly a distraction from the real work

The organizational energy being spent on AI is starting to crowd out the work AI was supposed to improve. Software engineers describe workplace paralysis from the release cadence alone (major releases have jumped from 18 in 2023 to 69 in 2025) and report spending more time learning, evaluating, and switching tools than building.

Middle managers are buried under oversight: validating AI output, coaching juniors who produce polished deliverables but cannot tell when the analysis is wrong, and interpreting what "AI-enhanced" means for client work with no firm-wide guidance.

The time juniors save producing output is consumed by managers checking it. Manager engagement has fallen from 30% to 22% in two years. Ninety percent of companies use AI in recruiting; fewer than 5% report transformational outcomes on any metric. The attention tax is real, and it is compounding. If your people are spending more time managing AI than doing the work AI is supposed to support, that is worth measuring before adding the next tool.

Quote of the Week:

This is the first time I have seen a technological innovation benefit older workers more than younger workers in terms of job security…All of that deep experience and expertise in a specific profession—but also in those soft skills of critical thinking and understanding at a systems level what’s happening—those are skills that older workers tend to have.”

—Heather Tinsley-Fix, AARP’s senior advisor of employer engagement, on the dilemma facing older workers whose soft skills may be rewarded amid the AI transformation: adapt or retire

Reading List:

Get ready for a wave of “physical AI”

The AI conversation has been dominated by software and knowledge work. The next phase is already getting physical. General Motors installed 50 robot arms at its flagship EV factory while 1,300 workers remain on temporary layoff. JD.com’s founder warned that the company’s 700,000 delivery workers will be replaced by robots sooner or later. Agility Robotics, which makes humanlike robots for warehouses, is going public at a $2.5 billion valuation.

Critical thinking is eroding

A study of 72,000 workers and found Gen Z and millennials are 18% below average in critical thinking, 17% below in attention to detail, 10% below in creative problem solving than other generations. Declining academic standards, weakened vocational pathways, and a generation that onboarded through Zoom rather than by watching experienced colleagues has create a clear but quiet crisis. Now they are using AI tools that produce polished output regardless of whether the judgment behind it is sound. Harvard Business School research confirms the risk: when bonuses depend on outcomes more than accuracy workers actively choose not to examine the AI’s reasoning.

We’re entering an uncompliable territory

Regulators are producing employment law faster than legal teams can implement it. California signed an executive order that could require 90 days' notice for AI-driven layoffs at a threshold of just 25 workers, New York passed a bill that bans companies from posting “fake” jobs, Michigan is debating a bill which makes it illegal to contact employers after work. In aggregate, they are pushing businesses toward a calculation European employers already make routinely: when does compliance risk cost less than compliance itself?

Data Point:

96%

Percentage of HR leaders that that, in the next five years, entry-level employees will be responsible for monitoring AI systems according to Cognizant

In Other News

• A 6 year study shows which CEOs are pushing RTO mandates: The ones with the biggest egos. (Fortune)

• Inside Consultants’ Messy Shift From Hourly Billing. (WSJ CFO Briefing)

• One in three entry-level tasks is now completed by AI: The adaptability imperative. (Cognizant)

• Our highly-paid, overworked junior staff keep leaving just as we get them fully trained. (Ask a Manager)

• AI Is Learning to Spot Toxic Bosses: Is sacrificing your own privacy worth it to stem your manager’s worst tendencies? (Bloomberg)

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By Ken Stibler; Powered by Reyvism

Leading people in an increasingly brittle economy

Companies are posting record profits yet laying off tens of thousands, and your employees are hearing all about it. Tech layoffs through May have already surpassed 115,000, running 44% faster than last year. But when Gallup asked laid-off workers directly what caused their layoff, and only 1% named AI. The more common answers were organizational restructuring, cost-cutting, and role elimination. Well quoted venture capitalist Marc Andreessen put a sharper point on it: most large companies are overstaffed by 25 to 50 percent, and AI has become the convenient cover story for cuts that were coming regardless. That is worth sitting with if you are a leader who has cited AI as the reason for a headcount decision, or is about to.

What makes this combustible is the environment those workers are worried about landing in. Only 22% of workers globally strongly agree their job is safe. Consumer prices jumped 4.2% in May, the highest in three years. Healthcare premiums are rising at double the rate of inflation. This economic climate is brittle to say the least, strip away AI-related spending and the economy has been in a recession for nearly 2 years.

Gallup data shows workers who used AI less than monthly were three times as likely to have been laid off as those who used it regularly. AI adoption is now a layoff risk factor, and most of your workforce does not know that. This is especially important for engaging those who stay.

We mined the comments of those laid off - a dataset of over a million comments over the last couple years - shows how much the layoffs felt like a rug pull, and are almost certain to lower the starting level of trust and engagement going forward.

Don’t give up on grads

Internship postings on Handshake fell 16% earlier this year, another double digital decline in a multi-year collapse in interns. In certain sectors, entry-level hiring has dropped more than 50% since 2019. The logic writes itself: AI handles the routine work that junior hires used to do, so why bring them in?

Yet the smartest money, hedge funds and leading firms, are starting to reverse course, seeing cutting entry-level programs as severing a key mechanism for transferring knowledge and building the next generation of people who actually understand how the work gets done. The routine tasks may go, but the judgment, the context, the institutional knowledge still have to come from somewhere, and are abut to get scarce.

Citadel just ran its largest intern cohort in the firm’s history, IBM is tripling its entry-level hiring this year. IBM’s CHRO put it plainly: “The companies three to five years from now that are going to be the most successful are those that doubled down on entry-level hiring in this environment.” The companies cutting their programs will have powerful tools in three years and no one who came up learning how to use them.

Quote of the Week:

“The goal cannot be surveillance for surveillance’s sake. The healthiest systems use assessment to support growth, mentorship, and adaptation. If workers only experience measurement without support, organizations create fear.”

— Carrol Chang, CEO of Andela

Reading List:

Hiring still happens but for increasingly narrow talent

Three in four CHROs expect hiring to concentrate in specific roles rather than expand broadly, according to a Conference Board survey of 111 CHROs. More than 70% say specialized technical roles are the hardest to fill. Only 21% of those who reduced hiring tied it to AI -- the majority cited financial caution. The Conference Board's own conclusion: skill requirements are evolving faster than talent pipelines, and anyone who cannot source this talent externally will have to build it internally. Most have not started. Shifting budget from recruiting to reskilling is the move, and it is easier to make before you are desperate for the skills than after.

Employers increasingly raise worker healthcare costs

Nearly half of large U.S. employers plan to shift more healthcare costs onto workers next year, according to Mercer's survey of 604 organizations. This is happening as workers are already squeezed by inflation, a low-hire market, and the job insecurity documented above. The timing matters. Workers currently blame insurers for rising costs, not employers…but that goodwill is not permanent. Cost-shifting does not reduce healthcare spend. It delays care, which drives up long-term costs and degrades productivity. If you are one of the organizations holding the line on benefits while competitors cut, that is a retention story worth telling your people explicitly.

Should you continually assess performance?

Airlines stopped measuring pilots by logged flight hours when cockpits became automated and started analyzing data from every flight to understand how they make decisions. HBR argues knowledge work is heading the same direction. The risk is Meta's mistake: a monitoring system employees experience as surveillance triggers backlash, not development. One CEO drew the line that "if workers only experience measurement without support, organizations create fear. If assessment is paired with coaching and transparency, people are much more willing to engage with change."

Data Point:

22%

Number of workers globally strongly agree that their job is safe from being eliminated according to the ADP People at Work 2026 report.

In Other News

• AI anxiety may be ramping up despite productivity hopes. (HR Dive)

• Mrs. Dow Jones: The American dream is ‘very dead’ for millennials and Gen Z. (Business Insider)

• Enterprises report increasing budgets for security training in AI and other critical topics. (CyberSecurityDive)

• Work From Home Is Here to Stay—Even if Some CEOs Don’t Love It. (Wall Street Journal)

• When Did White-Collar Work Start to Look So Bleak? In the nineteen-eighties, an office job promised security and fulfillment. For graduates starting careers today, the prospect is often tinged with dread. (New Yorker)

• This assumes the underlying data is right: Mistaking a Hiring Freeze for a Robot. (Apollo)

• I went viral on TikTok making $100 a day for 100 days by testing different side hustles — only 3 were worth sticking with. (Business Insider)

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By Ken Stibler; Powered by Reyvism

Leaders need a change strategy

I gave a speech this week and afterward the COO of one of the attendees pulled me aside. He wanted to talk, even though his company was already doing most of what I had recommended. That itself was notable. When I asked why they were so far ahead, I was ready to write it off as rare leadership and move on.

Then he named something that’s surprising for reasons I’m still not fully sure of: they had spun up a continuous improvement function years ago. That is the gap many leaders miss. Good leadership is a state whereas a continuous improvement function is a mechanism. One depends on the quality of the people in the room. The other runs regardless of who is in the room if done well.

“Oh no! Not another thing…” - CEOs

This is particularly important these days as the change is coming fast and from all directions at systems ill-prepared to handle it. The result is burnout at best if now downright risk:

• Rapid technological change is creating all sorts of changes that are far beyond the normal playbook: Companies aren’t prepared for how AI is accelerating the ability to impersonate CEOs for fraud. (HR Dive)

But change management (these days somewhere between incremental updates and holding on for dear life) is not the same thing as a change strategy is not a change management plan. A change strategy is the organizational infrastructure for making continuous change decisions well. It requires three things:

1. clear articulation of what will not change (the values, the talent philosophy, the trust compact with employees),

2. a structured process for evaluating what should change and at what pace,

3. and leadership accountability for the irreversible decisions.

The CEO from the first paragraph had all three. They did not build them in response to AI. They built them years earlier, and the AI transition was simply the latest input into a machine that was already running.

The practical implication is uncomfortable for leaders who prefer to move fast. Irreversible decisions, the ones that cannot be undone once made, require a higher bar of deliberation than reversible ones. Nobody said change at this rate was going to be comfortable, but it just might be less uncertain with the right structures.

AI-driven dis-engagement, Part 2

The new disengagement does not look like disengagement. Workers are busy, productivity metrics are up, but something is quietly eroding that’s hard to put your finger on.

Boston Consulting Group’s research calls it the joy paradox: 67% of workers report higher job satisfaction with AI, but 41% report a significant increase in cognitive load, and 47% say they spend more time managing AI than doing the actual work. Meanwhile, Penn State and USC researchers found that passive AI use (copying and pasting AI-generated responses) reduces feelings of ownership by 20% and meaningfulness by 10%.

Workers feel less connected to their output even when that output is better. And often its just replacing busy work more than being strategically valuable, white-collar employees spend 6.4 hours per week “botsitting,” managing AI output rather than producing, and one in three AI sessions fails completely.

The fix involved reorienting our relationship with the tools. Organizations that deploy AI as a productivity layer without redesigning workflows are trading long-term engagement for short-term output metrics. The 66% of employees given no guidance on what to do with AI-freed time are not being empowered. They are being left to drift.

Quote of the Week: More human, not less

“The skills that are most resistant to displacement by AI are the ones that are the most distinctly human: relationship building, conflict resolution, the ability to guide and motivate other people, and ethical judgment.”

— Maria Flynn, Jobs for the Future

Reading List:

What are tokens, why is everyone talking about them, and should you care?

Tokens are suddenly the “new thing” CEOs are being forced to think about. Simply put, tokens are the units vendors use to represent AI work and they are becoming the new headcount budgets. The top AI services are priced per token rather than per seat, which means the cost of AI scales with usage rather than with the number of employees who have access. Amazon recently cautioned its own employees against "tokenmaxxing," or using the most powerful models for tasks that do not require them.

Fortune 500s launch programs to own the labor as key shortages undermine growth strategies

Rather than lobbying for better workforce pipeline, Fortune 500 companies are increasingly building them…and in turn potentially controlling strategic talent supplies. With an estimated 2.1 million skilled trades jobs potentially going unfilled by 2030, the talent market cannot move fast enough. Meta, Bloomberg, and Ford are all investing in programs to offer free training and guaranteed jobs for every graduate in hot areas like data center construction.

GenZ's newest psychological feature: slow and steady?

44% of Gen Z prefer steady progress over fast-paced promotions, and 55% are delaying major life decisions due to economic uncertainty according to the 2026 Deloitte Gen Z and Millennial Survey. The instinct is to read this as a lack of ambition. It is more accurately read as a rational response to the environment they inherited. Gen Z entered the workforce during a pandemic, watched the mass layoffs of 2023-2024 eliminate people who had done everything right, and is now navigating an AI transition that makes career planning genuinely uncertain.

Data Point: “Botsitting”

6.4

Number of hours white-collar workers spend per week "botsitting" (managing AI output rather than producing work) according the Glean Work AI Index.

In Other News

• People who eagerly seek out managerial positions may be least suited for the roles. (HR Dive)

• Doomjobbing Report: 48% of Job Seekers Apply Without Reading the Full Job Description. (Monster)

• Labor market adds 172,000 jobs in May, but growth remains uneven: Most industries saw no changes or declines in total employment. (HR Brew)

• Making the case for fractional and AI employees: At New York Tech Week, a panel focused on how startups can benefit from workers—agentic or otherwise—who aren’t on the full-time payroll. (HR Brew)

• More Employees Embrace ‘Microshifting,’ Carving Their Workday Into Chunks: The hope is that it can help people produce better work, while preventing burnout and turnover. (Wall Street Journal)

• New York passes a bill aimed at halting ‘ghost jobs’. (HR Dive)

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By Ken Stibler; Powered by Reyvism

How do we know what should stay the same and what should change?

This question is probably harder to answer now than it has ever been, and not for the reason most people cite. The pace of change is obvious. What is less obvious is that the cost of being wrong has become asymmetric. In a stable environment, if you change something that should have stayed the same, you reverse it. The cost is friction and some lost time. In the current environment, some changes are irreversible.

You cannot un-fire 17% of your workforce. You cannot un-break the trust compact once employees have watched you track their mouse clicks and walked it back. You cannot un-signal to your best people that they are disposable.

These are real cases. Meta reversed course on an employee mouse-tracking tool after internal backlash. The policy was reversible. The damage to the psychological contract was not. Microsoft omitted a question from an internal survey about whether leadership was listening and got (ironically) hammered for it. They can add the question back. The signal about what leadership is willing to hear is harder to take back. Snowflake’s CIO threatened layoffs to force AI adoption. Whether the signal and rise in ChatGPT use is worth it remains debatable.

We don’t have a perfect answer to this question. However the leaders we see doing this well are the ones who have a clear mental model of what is reversible and what is not, and they apply that model before they act. The practical discipline is simple: before any significant change, ask whether it can be undone.

If the answer is no, the bar for needing to proceed should be much higher. The changes that look bold in the short term and are genuinely irreversible in their human consequences deserve the most scrutiny, not the least.

The strategic value of variance

Artificial intelligence is an engine of sameness. Just like a good manager, it trains on what good is, optimizes for reliability, and produces the expected. In many operational functions, that consistency is a feature. But in strategy, design, and human capital, that consistency is sneakily becoming a strategic risk.

When every organization has access to the same models, the same prompts, and the same generated patterns, the baseline of acceptable work rises, but the ceiling of differentiated work becomes harder to reach. Wharton research on user experience design highlights this trap: AI can accelerate the creation of competent, me-too experiences, but it systematically compresses the productive variance that leads to breakthroughs. The same dynamic applies to talent. Workers increasingly prefer AI feedback because it is less judgmental, but a culture optimized for comfort over candor will eventually lose its edge.

The best path forward is to augment the baseline, but deliberately introduce human friction, divergent thinking, and non-consensus decision-making into their most critical processes. Differentiation requires variance, and variance requires humans.

Quote of the Week: One foot in, one foot out

"I hate the word balance. If you can finish everything before you go to sleep, you don't have an interesting enough job."

— Arianna Huffington, Founder and CEO of Thrive Global

Reading List:

Spending more than your G&A budget on AI

So-called tokenmaxxing (quick note: genzs have taken to adding the term “maxxing” onto any word to imply doing it extensively) is on the rise. Stupid name aside, the phenomenon of spending any amount of money on AI credits is leaving some companies with some head scratching numbers. Last week it came out that one Fortune 500 company spend half a billion dollars on AI credits. When you are spending more on AI than all G&A and labor costs combined, the “efficiency” thesis of adoption needs to be seriously re-considered

Employees can now reject AI for religious reasons

When a North Carolina software engineer secures an exemption to avoid using AI at work on religious grounds it sounds silly. But the legal implications of Pope Leo XIV's encyclical are serious. What the pope did with this formal decry was offering a written theological argument to around 60 million Catholic workers in America. Under Title VII, employers must accommodate sincerely held religious beliefs unless doing so causes undue hardship. If you are mandating AI use across your workforce, get ready for a rise in exemptions and potentially legal risk if it’s treated it as a condition of employment.

Culture plots its revenge in the efficiency era

The efficiency era has treated culture as a soft variable to be managed after the structural cuts are made, but McKinsey research shows companies with strong, aligned cultures are three times more likely to deliver superior total shareholder return. Culture is not the backdrop to strategy. It is the operating system, and the efficiency era's habit of treating it as an afterthought is accumulating a debt that will show up in execution long before it shows up in earnings.

Data Point:

200

The number of metropolitan areas where unemployment rates were higher in April 2026 than a year earlier, according to the Bureau of Labor Statistics, signaling a broader cooling in the labor market outside of a few high growth areas.

Beyond hiring that divide is critical for understanding geographic differences in spending for sales targeting.

In Other News

• These COOs became CEOs. Here’s what they wish everyone knew about the tricky transition. (CEO Daily)

• Leaders who can’t see worker problems are creating a ‘dignity debt. (HR Dive)

• 1 in 4 White-Collar Workers Are Stalling Out: Invisible barrier keeping many Americans from getting ahead—midcareer stall. (Wall Street Journal)

• A Three-Minute Protocol to Reduce AI Manipulation Risk: A simple critical-thinking habit can protect employees and organizations from AI-enabled deception and manipulation. (MIT Sloan)

• Rising healthcare costs are prompting HR to rethink benefits strategies: Three-fourths of employers think they’re doing enough to help mitigate medical costs, but only 46% of employees agree. (HR Brew)

• ‘I’ve applied for more than 400 roles’ - how young people are facing the job shortage. (BBC)

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By Ken Stibler; Powered by Reyvism Analytics

Supporting your employees when everyone is overwhelmed

When we sit down to write this newsletter each week, there is a hesitant calculus about what is worth bring to you. Our audience skews heavily executive. We are always considering the fact that each new problem we bring up, or even action proposed, is pulling from an already depleted ability to do much with it in most workplaces.

This is especially difficult as an era of layoffs, geopolitical unrest, AI-fueled uncertainty, and unrelenting pressure to deliver leaves little room for anything else. Asking people to think about their career development on top of everything feels impossible. But supporting your team’s growth is an essential part of your job. The question is how to make career development feel relevant rather than tone-deaf when your own plate is just as full.

The answer is to stop treating learning as an extracurricular activity. Helen Tupper, cofounder of career development consultancy Amazing If, notes that most employees know they should be building new skills, but the demands of the here and now leave little room for it. They put their day job over their development.

The solution is to build learning into the week, not onto it. Look at their calendar. There is almost certainly something already coming up, such as a client event or a presentation, where they could play a bigger part. Let them open the meeting, lead the Q&A, or debrief the client. When it is done, make sure you take the time to reflect on it together.

And since you are figuring it out too, resist the urge to pretend otherwise. Share what you are currently reading or working on. Talk about a conversation that challenged your thinking. Be open about a mistake and what you took from it. As Tupper puts it: “Learning can look like anything, as long as they can see you doing it.”

How can learning compete in an attention deficit?

Workplace training has a TikTok problem. Learning experiences were designed in an era when social media exist and there weren’t a host of tools we have now to present complex ideas in genuinely entertaining ways. Now, people are scrolling constantly, consuming content that is fast, personally relevant, emotionally engaging, and designed by teams who understand human attention down to the millisecond.

When employees are asked to sit through dense modules and generic slides that feel like they were built before color TV, the disconnect is obvious. Low engagement with training is likely as much an issue of bland resources and boring design that do not feel worthwhile, as of being busy.

For the future of trainings, creativity, story-led content, and direct relevance to those taking it are better than completeness. On that note, measure impact rather than just completion is key to make learning more than just a box to check. Completion rates alone tell us very little about whether learning has actually had an impact.

Quote of the Week: Not how I’d roll out AI

Standard Chartered CEO Bill Winters apologized for offending colleagues and strangers alike when he said the British bank’s aim with using AI is to partly replace “lower-value human capital.”

Reading List:

HR invests more time in training as “skill engagement” becomes a rare point of workplace alignment

The share of HR leaders naming employee training their top priority jumped nearly 90% since last year. AI is the driver: it is increasing role complexity faster than existing programs were designed for. A Go1 survey of 2,000 L&D leaders found 7 in 10 professionals use AI weekly, but only 14% consider themselves advanced users. The organizations making the strongest progress are treating workforce capability as infrastructure, not a budget line that fluctuates with hiring.

CEOs get ruthless about performance

The corporate ethos of the previous decade, when leaders put empathy out front while quietly wishing employees worked harder, is over. As AI gives employers more leverage in a sluggish white-collar market, a growing chorus of CEOs is saying the quiet part out loud. Nestle's Philipp Navratil pledged to be "ruthless in assessing talent." Citigroup's Jane Fraser reminded staff they are judged on results, not effort. Executives used the phrase "performance culture" 633 times on S&P 500 earnings calls last year, up from 460 the year before. B-players are being managed out.

Don’t let yourself go numb, or back to sleep on AI’s disruption

There is a lot of noise right about AI right now, but the cost of tuning it out is rising too. Adecco Group research across 2,000 C-suite executives shows a widening gap between what leaders expect AI to deliver and what their organizations can actually do. While 45% of leaders expect AI agents integrated into workflows within a year, less than a third of workers agree, and only 36% of leaders say their talent strategy clearly shows how AI creates opportunity rather than displacement. "AI may move at software speed," Adecco CEO Denis Machuel said, "but organizational trust moves at human speed."

Data Point: Even the summer camps aren’t hiring

30%

Year on year fall in camp counsel jobs indicating a rough climate for teens looking for a summer job. Literally EVERYONE is affected in this economy.

In Other News

• ‘I live in survival mode’: The rise of the multi-job workforce. (BBC)

• The 19th-century guide to running an effective meeting: A US officer and engineer devised the process that is still in use today. (Financial Times)

• Target plans to evaluate employees on customer engagement. (HR Dive)

• More workers are raiding their 401(k)s as average balances fall, Fidelity says. (CNBC)

• Bolt CEO says he let go of his entire HR team for creating problems that didn’t exist: ‘Those problems disappeared when I let them go’. (Fortune)

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By Ken Stibler; Powered by Reyvism Analytics

Creating employee engagement during a culture of fear

When former Google CEO Eric Schmidt was booed during a graduation speech about AI, it was as much a protest against a technology as it was signal that uncertainty is fast metastasizing into fear. The fear is justified. Customer service roles fell 130,180 in the year through May 2025. Credit authorizers are down 26.2% since ChatGPT’s introduction. The playbook is visible: Intuit cut 17% of its staff, targeting mid-level managers. Meta laid off thousands and moved managers to IC roles. As one Capital One employee virally posted: “This is exactly why you should never sacrifice too much for these companies. You are always disposable to them.”

And to a degree it’s true, isn’t it?

The question is what the new compact looks like. Sophos CEO Joe Levy faces this directly. When employees ask if support jobs will be eliminated, his answer is honest: “I don’t know.” Instead of false promises, Sophos uses a four-part framework: provide tools, give training, share examples, and offer incentives. Most companies stop after the first two. Sophos goes further because “What should I do with it?” is the most common question. They make AI part of performance reviews, measuring both outcomes and the process of finding efficiencies.

The leadership challenge is maintaining engagement when the workforce assumes they are being automated out. The answer is not pretending the threat does not exist. It is giving employees agency over the transition. Leaders who admit uncertainty but provide tools and incentives for employees to figure it out alongside them replace paralyzing fear with productive experimentation.

Fast adoption and poor governance kicks AI risks to HR departments…or legal

Get ready for shadow AI. Verizon data shows a fourfold increase in non-malicious insider actions tied to unauthorized AI use. Of the 45% of professionals using AI regularly, 67% access platforms via unauthorized personal accounts. Workers with access to sensitive material are plugging it into their tool of choice, leaving their organization blind to the exposure.

The risks are concrete: 28% of data loss prevention violations involved employees entering source code into AI tools. In 3.2% of cases, workers uploaded proprietary research. Yet only 13% of organizations have adequate AI agent governance. The gap is driving the development of AI-BOMs to track configurations and system prompts. Until governance catches up to adoption, IP loss and compliance violations will land on HR and legal.

Quote of the Week:

"We as employers aren't doing a good enough job saying [to older workers], we value the skills that you already have, so much so that we want to invest in you to help you do your job better."

— Becky Frankiewicz, Chief Strategy Officer at ManpowerGroup

Reading List:

Workers contend with ‘skill atrophy’

There is a vicious cycle forming in AI adoption. A new GoTo survey found that 60% of employees feel pressured to use AI for productivity, yet 39% say the reliance has already weakened their skill sets. Half acknowledge they depend too heavily on the technology. The pressure to adopt is eroding the very capabilities that make human judgment valuable. While “perishable” skills tied to specific tools will be replaced regardless, but durable skills like judgment, critical thinking, and decision-making are what will differentiate high performers in an AI-saturated workplace.

Despite public examples, most employers are not cutting paid leave

When Zoom cut parental leave from 22 to 18 weeks and Deloitte halved theirs from 16 to 8, it felt like the start of a trend. It is not. A Marsh McLennan Agency survey found 86% of firms have no plans to change vacation time and 93% will maintain sick leave levels. The legal environment is part of the reason: 12 or more states now mandate paid family and medical leave, and 18 require paid sick leave, making cuts both complex and risky. If your organization is holding the line while competitors cut back, that is a story worth telling your employees.

When it comes to leadership, replacement is abdication

The most relevant AI risk for leaders might be abdication more than competitive effects. Data finds that leaders who outsource judgment to AI - out of fear of obsolescence - become less trusted by their teams. AI can generate, optimize, and even mimic wisdom. But it cannot hesitate, doubt, or read a room.

Data Point:

67%

Number of professionals who use AI regularly are accessing platforms using unauthorized personal accounts.

In Other News

• Indeed parent company touts record growth driven by AI. (HR Dive)

• Bolt’s cofounder scrapped its HR department. This CEO says people management is key to thriving in the AI age. (CEO Daily)

• Meta is rapidly reorganizing its workers’ jobs around AI: ‘Transfers aren’t optional’. (The Guardian)

• LinkedIn declares war on AI slop: The job networking site plans to target low-quality AI posts that distract its users from finding value on the platform. (Fast Company)

• While other tech CEOs warn of mass job losses, Glean’s chief says AI will never replace a single worker. (Fortune)