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Duncan Trevithick, a marketing professional for an AI training data company based in Spain, finds himself in a peculiar position: his year-end bonus is contingent on his proficiency in utilizing Artificial Intelligence at work. The prospect of increased tasks completed with greater speed is presented as a lucrative incentive, yet Trevithick voices a fundamental concern: what truly benefits him in this evolving landscape? He articulates a disquieting interpretation, suggesting that employees are being evaluated on their capacity to facilitate their own potential redundancy. Should he leverage AI to complete two days’ worth of work each week, the financial rewards, he argues, simply do not equate to the value generated. He points out that he doesn’t receive two extra days off or a 40% salary increase; instead, the heightened output merely becomes the new standard. While this might offer a short-term boost for promotion, he contends that in the long run, he has inadvertently demonstrated the diminishing necessity of his role. His perspective shifts to that of a manager, overseeing not only human colleagues but also AI agents or "AI loops."
The practice of assessing employees’ AI capabilities for bonuses, promotions, or even dismissals is rapidly becoming a widespread phenomenon. Julie Sweet, CEO of Accenture, stated in March that AI is now integral to how work is performed within the company, implying that promotion hinges on embracing these new operational methods. Prominent corporations such as Disney, Meta, JP Morgan, and KPMG have reportedly established "AI leaderboards" to monitor and rank employee engagement with various Large Language Models (LLMs) and AI platforms. This trend is driven by a palpable urgency among business leaders to realize a return on their significant AI investments, particularly in light of a McKinsey report indicating that a substantial 94% of companies have yet to derive significant value from AI. The current job market further compels employees to adapt. In the UK, for instance, job vacancies have reached a five-year low. A poll of 1,881 UK jobseekers revealed that a significant majority (75%) would not be deterred from applying to organizations that incorporate AI proficiency into performance reviews, with only 22% expressing reservations. Trevithick likens this situation to being caught in a powerful wave, where the only options are to try and ride it or be overwhelmed, acknowledging that stopping it is not feasible.
The subtle yet impactful shifts occurring within large organizations are causing unease for many employees. Pamela, a senior executive in the US (whose name has been changed to protect her identity), observes that while no explicit mandate exists for AI adoption, it is undeniably influencing who receives recognition and who is left behind. She describes the professional landscape as "shifting under us," emphasizing the growing importance of demonstrating AI fluency and adaptability as a key achievement. Although there’s no overt threat of "learn AI or else," Pamela asserts that performance reviews unequivocally reward effective AI utilization. This evolution, she notes, is elevating AI capabilities above traditional experience, creating a discernible "two-tier workforce." Employees with identical job titles and tenure are being valued differently based on their perception of AI – whether as a threat or a tool – a gap that widens rapidly once leadership takes notice. Pamela contends that AI fluency now surpasses credentials, with individuals possessing limited experience but strong AI skills being favored over those with decades of experience but lacking AI proficiency. Consequently, employees who are not visibly engaging with AI face slower promotion trajectories, reduced visibility, and a diminished chance of being shortlisted for opportunities.
The legality of companies altering performance benchmarks in this manner is a pertinent question. Tina Chander, an employment lawyer and partner at Weightmans, confirms that legally, employers are within their rights. However, this practice raises significant questions regarding pay equity and fairness. Chander probes whether it is equitable for employers to increase work expectations based on an employee’s enhanced efficiency through AI. She further questions whether employees who are effectively accomplishing more due to AI-driven productivity gains should receive different compensation or if, conversely, they are inadvertently making themselves redundant, thereby creating a disincentive for productivity. Chander strongly advises businesses to implement clear policies, provide comprehensive training, and establish defined boundaries to mitigate the risk of employees initiating disputes over fairness, performance expectations, and job security. This advice is particularly relevant given upcoming changes in UK employment law, where the window for unfair dismissal claims will expand from three to six months, and employees will be eligible to file such claims after only six months of service, a reduction from the current two years, effective from January 2027.
HR consultant Tina Rahman highlights a critical lack of transparency from employers regarding the rationale behind integrating AI into their workforce and its ultimate objectives, which she identifies as cost and time savings, as well as a reduction in outsourcing. She believes this lack of clarity leads to employee misunderstanding and apprehension. Rahman, who heads HR Habitat, a London-based consultancy, emphasizes that the true purpose of AI integration is not being effectively communicated to employees. This opacity is indeed fueling discontent within organizations like Pamela’s. Pamela observes that leadership is deliberately being inconsistent and vague, aiming for productivity gains without taking ownership of the ensuing disruption. This creates a scenario where, if something goes wrong, leadership can disavow responsibility, while successful AI implementations are met with approval.
Kamila Miller, an applied AI researcher and lecturer at Henley Business School, warns that mandating AI usage can devolve into a performative exercise devoid of genuine positive impact. She argues that making AI usage a Key Performance Indicator (KPI) can lead employees to merely log interactions to meet the metric, route non-essential work through chatbots, and generate AI-enhanced outputs that appear productive on dashboards. This approach, Miller states, measures adoption rather than critical judgment, learning, or improved decision-making, ultimately making employees more obedient rather than more skilled.
Fortunately, some organizations are recognizing these concerns. In April, Luis von Ahn, CEO of Duolingo, revealed that the language learning company had ceased using AI usage as a criterion in performance reviews. He explained that employees were questioning the purpose of using AI "for AI’s sake." Duolingo ultimately reverted to prioritizing the core performance of an employee’s role, acknowledging that AI can be a valuable aid but should not be forced if it doesn’t enhance performance. Similarly, in May, the Financial Times reported that Amazon had discontinued an internal leaderboard that tracked employee AI usage, as staff were reportedly attempting to artificially inflate their rankings by assigning AI tasks that were unnecessary.
Despite these high-profile reversals, a sense of necessity persists for many employees to demonstrate AI proficiency. Pamela, in her mid-50s and planning to retire within a decade, is focused on job security to protect her pension and health benefits. She is actively showcasing how AI assists her in acquiring new clients and ensuring she receives due credit for these successes. Duncan Trevithick, on his part, is actively engaged in side projects to future-proof his career. He acknowledges that in a capitalist model, if AI can perform a job more effectively, businesses will naturally opt for replacement. Therefore, he believes the strategic imperative is to transition into roles where individuals can leverage and benefit from AI by owning assets that utilize it.
George Anjay
Nakalama John
Ramos Leo