Companies Are Starting to Enforce AI Use. Is that a Good or Bad Thing?
A weekly round-up of news, perspectives, predictions, and provocations on AI's impact on employee wellbeing, readiness and performance.
Years ago, I was working on the editorial side for what was then a hot new media company, and found myself spending more and more time with Johan, the lead programmer, and his team, asking them a lot of annoying questions as it was all so new – certainly to me. I was standing over Johan’s left shoulder, mesmerized by whatever new video game he was obsessing over that week…when suddenly, out of nowhere, a spreadsheet and a pie chart appeared on his screen.
“Whatcha got there, Johan?” asked Jim, Johan’s boss, peering over a sheaf of print-outs as he sharked past the cubicle.
“Hey, just looking at some numbers,” Johan replied. Johan had hit the “game key” in the nick of time – in those days, every video game had a game key – ALT-G if memory serves - calling up a slight variation of the same spreadsheet and pie chart.
This would never happen today. First, you’re probably not working in a cubicle, and if you are, it’s not the game key you’d hit to give your boss the impression that you’re actually doing productive work…it would be the “AI key.”
“Tech Firms Aren’t Just Encouraging Their Workers to Use AI. They’re Enforcing It.”
This article appeared in the February 24 edition of the Wall Street Journal. It includes the subtitle: From startups to giants, including Meta and Google, companies are factoring AI use into performance reviews and trying to track productivity gains
Across industries, companies are now enforcing AI use through performance reviews, dashboards that track adoption, and explicit mandates that tie it to compensation and promotion. What began in Silicon Valley has rapidly spread to consulting firms, banks, manufacturers, hospitals, and even government agencies.
As you’d expect, Meta, Google, Amazon, and Microsoft were the first to move from encouragement to enforcement. Employees at these firms now see AI usage metrics appear in quarterly reviews. Non-adopters have reported stalled promotions or explicit warnings that “AI fluency” is a core competency (The Wall Street Journal, Feb 2026, reporting on internal policies).
The trend has jumped sectors. PwC requires every consultant to complete an “AI + Human Skillset” curriculum and incorporates usage into evaluations (Business Insider, Feb 5, 2026). Colgate-Palmolive’s “AI evangelist” tracks adoption across global teams. Major banks have begun tying bonuses to the number of AI-assisted analyses completed. Even some hospitals now require doctors and nurses to use AI-assisted diagnostic tools for certain procedures.
Why the shift to mandates?
Executives cite three main drivers: intense competitive pressure to keep pace with rivals, investor demands for visible returns on massive AI investments, and internal data showing that voluntary adoption plateaus at around 30–40% of employees. “We’ve made it clear: AI is no longer optional. Every employee is expected to use it, and it’s now part of how we evaluate performance,” said Accenture CEO Julie Sweet (Fortune, March 2026).
The claimed benefits are real…on paper. Early internal metrics at several companies show 10–25% gains in task speed for routine work. Cross-functional teams using AI report faster ideation and fewer silos. But the drawbacks and unintended consequences are mounting.
While mandatory AI adoption offers productivity benefits, recent research reveals significant drawbacks that undermine organizational health.
Surveillance and autonomy erosion. By 2025, 70% of large companies monitor employee activity, with 68% of employees opposing AI-powered surveillance and 59% saying digital tracking damages workplace trust. AI monitoring systems now track keystroke patterns, mouse movements, email content, and even biometric data, including stress levels. Amazon employees report that surveillance creates “fear and anxiety, which creates a dangerous work environment”.
Burnout and intensified demands. AI meant to reduce workload is paradoxically accelerating burnout. Research found that AI leads to fatigue, burnout, and a growing sense that work is harder to step away from as organizational expectations for speed rise. A South Korean study shows AI adoption significantly increases job stress and burnout, while 63% of workers report AI-related fatigue driven by stress and heavy workloads.
Collapsing trust. Recent research revealed that while AI usage jumped 13% in 2025, worker confidence plummeted 18%, creating a “toxic relationship” as employees receive tools without training or support. Deloitte’s TrustID Index showed trust in company-provided generative AI fell 31% between May and July 2025, with trust in agentic AI systems dropping 89%.
Retention risks. Without adequate training, 56% of workers receive no recent skills development despite widespread AI adoption, and 85% say they would be more loyal to employers investing in continuing education - top performers become increasingly vulnerable to departure. Analysis warns of an impending “seniority cliff” as companies that stop hiring juniors eliminate the pipeline for developing senior talent with deep institutional knowledge.
Critics argue the enforcement model is shortsighted.
“You can force usage, but you can’t force wisdom,” said Dr. Ethan Mollick, professor at the Wharton School and author of Co-Intelligence (interview, March 2026). “When AI becomes compulsory, people stop experimenting and start complying — and that’s when the real mistakes happen.” Yet the train has left the station. In boardrooms and earnings calls, executives are increasingly judged on how aggressively they have embedded AI into daily operations.
The message is clear: in 2026, using AI is part of your job. The question companies are only beginning to confront is whether forcing the technology will ultimately make their workforces more cohesive, smarter, and more efficient, or simply more exhausted, distrustful, and replaceable.
AI Gone Rogue
Tales of AI being unintentionally funny (i.e., woefully wrong), bizarre, creepy, (amusingly) scary, and/or just plain scary.
ChatGPT Health fails to recognise medical emergencies in over half of cases.
A new study found ChatGPT Health missed critical emergency signs in more than 50% of tested scenarios, alarming doctors about life-threatening risks in AI health tools. Source: The Guardian
ChatGPT Health regularly misses the need for medical urgent care and frequently fails to detect suicidal ideation, a study of the AI platform has found, which experts worry could “feasibly lead to unnecessary harm and death”.
OpenAI launched the “Health” feature of ChatGPT to limited audiences in January, which it promotes as a way for users to “securely connect medical records and wellness apps” to generate health advice and responses. More than 40 million people reportedly ask ChatGPT for health-related advice every day.
The first independent safety evaluation of ChatGPT Health, published in the February edition of the journal Nature Medicine, found it under-triaged more than half of the cases presented to it.
From Anxiety to Agency: Improving Employee Readiness in the Age of AI
HR Rebooted’s founder and CEO, Michelle Strasburger, joined us on the maiden AI4HR Live virtual event to discuss the relationship between AI governance and readiness at the organisational, leadership, and employee levels. You can view it here.
Register here for our next session, Why Tech Transitions Fail: The Hidden Psychology of Platform Change. It will be held on March 31, 2026, at 11:00 AM - 11:30 AM ET.
AIX-emplary Links
The week’s most interesting and timely articles on AI and readiness.
Accenture CEO says AI adoption is now required for promotion. Accenture ties AI proficiency directly to promotions and performance reviews, accelerating mandatory upskilling while exiting employees who resist adoption. Source: Fortune
Your Employees Aren’t Resisting AI. The real barrier to readiness is an identity crisis among workers; leaders must address emotional and psychological factors beyond training to close adoption gaps. Source: Inc.
The key to companywide AI adoption? Empowering managers. Managers experiment with AI far more than employees; HR must equip frontline leaders to drive readiness and bridge the usage gap. Source: HR Dive
The Next Phase of the AI Boom: Testing Employees’ Ability to Use It
Companies shift from adoption hype to measuring actual employee AI fluency, marking the next phase of workforce readiness assessment. Source: Business InsiderThe AI Adoption Gap: AI Can Do More Than Companies Allow. Anthropic research shows organizations underutilize AI’s capabilities due to structural barriers; readiness requires operating-model changes beyond tools. Source: Forbes
AI washing in the workplace: when “AI made us do it” is not enough. Companies increasingly blame AI for workforce changes; readiness requires transparency to avoid backlash and maintain trust. Source: Lexology
Closing the AI Skills Gap. State-level collaborations demonstrate education as the core strategy for responsible AI adoption and workforce readiness. Source: Connected World
CEOs are mandating that employees use AI. They’re hardly using it themselves.
Executives push mandatory AI use while personally using it less than an hour weekly, revealing a leadership readiness disconnect. Source: FortuneAI Adoption Rapidly Growing in Public Sector. Public-sector AI use now nears private-sector levels, but managerial support and strategy remain critical for true readiness. Source: Gallup
AI Is Forcing Employees to Work Harder Than Ever
Research shows AI adds oversight and complexity, intensifying workloads and highlighting the gap between adoption and true readiness. Source: FuturismThe AI Productivity Paradox: More work, not less. AI compresses tasks but creates new cognitive demands; readiness requires redesigning workflows to prevent “AI brain fry.” Source: Fortune
About
Developed in partnership with HR.com, AIX is a multimedia knowledge and engagement platform for experts, leaders, and HR peers to exchange experiences and seek guidance on cultivating mentally resilient, emotionally intelligent, and professionally adaptable workforces in an AI-augmented world. AI will increasingly touch every corner of the employee experience—from hiring to training, from task management to team dynamics. Whether its impact is positive or harmful depends largely on how HR prepares for it. The AIX platform (The AIX Files, The AIX Factor podcast, and the AIXonHR.com community) will play an important role in promoting employee well-being, workplace culture, and organisational readiness, the critical success factors in the age of AI.
The mandated adoption angle is interesting because it creates burnout from a different direction. Voluntary AI users hit cognitive overload from doing too much. Mandated users hit it from surveillance anxiety and forced workflow changes they didn't choose.
Trust dropping 18% despite usage going up 13% is the number that stands out. People are using it more and trusting it less. That gap is where the real productivity paradox lives. More on what that looks like at individual scale: https://thoughts.jock.pl/p/ai-productivity-paradox-wellbeing-agent-age-2026
Forcing adoption without redesigning the work around it just creates exhaustion faster.
I feel like this approach is happening but we're missing a key component. Governance. Adoption is not happening because of a multitude of reasons, but it's not because my boss is not telling me to use it. "Because I said so" doesn't work as a parent and it won't work as a boss. Meeting the employee where they're at and finding out the barriers to adoption and building solutions in your governance plans is the only way this will work. Take our gap analysis at www.hrrebooted.com to see where you're falling short on Governance. I promise you, It's not "I told you so!"