It’s in Duncan Trevithick’s interest to excel at using AI at work. If he can complete more tasks faster, he stands to earn a year-end bonus.
On the surface, the incentive looks attractive. Yet Trevithick questions what he truly gains.
“The uncomfortable interpretation is that employees are being assessed on how effectively they can participate in their own redundancy,” says the 34-year-old, who works in marketing for an AI training-data company from Spain.
If AI handles two days’ worth of work each week, he notes, the financial rewards do not match the extra output. “I do not receive two days off or a 40% pay rise. The higher output simply becomes the new baseline. In the short term, that may help me get promoted. In the longer term, I have helped prove how much of my job no longer requires me.”
He tries to reframe his role: “I’m just trying to view myself as a manager, and I’m managing some people, and I’m also managing AI agents, or AI loops, or whatever you want to call it.”
Using employees’ AI skills as a criterion for bonuses, promotions—or even dismissal—is becoming increasingly common.
Accenture CEO Julie Sweet told the *Rapid Response* podcast in March: “Today, AI at Accenture is how we do work. So if you want to get promoted, you’ve got to do the things that we do to operate at Accenture.”
Disney, Meta, JPMorgan and KPMG have introduced “AI leaderboards” that rank staff according to their use of large language models and other platforms, according to media reports. Crypto exchange Coinbase has already dismissed engineers who failed to complete mandatory AI training ordered by chief executive Brian Armstrong.
The trend reflects leaders’ urgency to extract returns from AI investments. McKinsey reports that 94% of companies have yet to realise significant value from the technology.
Employees feel pressure to adapt, particularly in a tight labour market. In the UK, job vacancies have fallen to a five-year low. A July poll of 1,881 UK jobseekers by recruiter Gi Group found that 75% would not be deterred by an employer that factored AI proficiency into performance reviews; only 22% said it would put them off.
“It’s like being in the sea, and you see a giant wave coming,” Trevithick says. “You can get out a surfboard and try and ride it as long as possible, or you can just let it take you under. But you can’t stop the wave.”
At the large consultancy where Pamela (not her real name) works as a senior executive in the United States, the shift feels more subtle but no less consequential. There is no formal mandate to use AI, yet it clearly influences who is rewarded and who is overlooked.
“The ground is shifting under us. You’ve got to demonstrate [AI] fluency and fluidity as one of your key achievements. It’s kind of quiet where nobody’s saying, ‘learn AI or else’. But let me tell you, in performance reviews, they reward who uses it well.”
The result, she says, is a two-tier workforce. “You’ve got the same job title, same tenure, but different value based on whether someone treats AI as a threat or a tool—that gap widens really quickly once leadership notices it.
“AI fluency beats credentials every day. Somebody that has 15, 20 years of experience and no AI fluency will be passed over for those that have, say, three years, but are fast with the tools.”
Visible non-use of AI, she adds, slows promotion timelines: “It’s harder to be seen, and it’s harder to fight being on that shortlist.”
Is such a change in expectations lawful? Tina Chander, partner and employment lawyer at Weightmans, confirms that employers are legally free to adjust criteria. The real issues centre on fairness and pay.
“The question then becomes whether the employer increases expectations on the basis that the employee can now produce more work. Is that fair? And if an employee is effectively doing more because AI has made them more efficient, should they be rewarded differently? Or are they effectively making themselves redundant, thus acting as a disincentive to be productive?”
Chander urges companies to set clear policies, provide training and define boundaries. Without them, disputes over fairness, performance standards and job security are more likely. From January 2027, UK employees will be able to claim unfair dismissal after only six months’ service (instead of two years) and will have six months rather than three to lodge a claim.
HR consultant Tina Rahman argues that many employers still fail to explain why AI is being integrated into roles and what the ultimate purpose is—chiefly cost and time savings, plus reduced reliance on outsourcing.
“Because they misunderstand it, this is not being reflected to employees,” says Rahman, who runs London-based consultancy HR Habitat.
That lack of clarity fuels discontent at Pamela’s firm. “Leadership is being inconsistent and vague on purpose. Firms want productivity gains without owning the disruption narrative. If something goes wrong, they’re going to say, ‘I didn’t tell you to do that. Where’d you get that from?’ Then if you did something with AI, and it works, great.”
Mandating AI use can also become performative, warns Kamila Miller, applied AI researcher and lecturer at Henley Business School.
“Make AI usage a KPI, and people will log their interactions to hit the metric, route work through a chatbot that did not need it, and generate AI-flavoured outputs that look productive on a dashboard. You will measure adoption. You will not measure judgement, learning, or better decisions. You have not made people more skilled—you have made them more obedient.”
Some organisations have recognised the problem. In April, Duolingo CEO Luis von Ahn told the *Silicon Valley Girl* podcast that the company had stopped treating AI use as a performance criterion.
“We found that people… were asking: ‘Do you want us to use AI for AI’s sake?’ In the end we backtracked, and we said: ‘Look, the most important thing for your performance is that you are doing, whatever your job is, as well as possible. A lot of times AI can help you with that. But if it can’t, I’m not going to force you to do that.’”
In May, the *Financial Times* reported that Amazon had dismantled an internal leaderboard tracking staff AI usage after employees began creating unnecessary tasks simply to climb the rankings.
Despite these high-profile reversals, many employees still feel compelled to demonstrate AI proficiency. Pamela, now in her mid-50s and planning to retire within a decade, is deliberately increasing her visible use of AI to win new clients so she can protect her pension and health benefits.
Trevithick, meanwhile, is building side projects as a form of insurance. “If AI can do a job better than you can, it makes sense for the business to replace you. That’s how the capitalist model works. So it’s about how you can move into a position where you own assets, where you can leverage AI, and then you benefit.”