Promotion is tied to AI adoption as usage metrics push employees toward showy productivity

Major global companies are accelerating the linking of employee evaluations and annual promotions to their use of AI tools, in a direct effort to push staff toward adopting generative models in daily tasks. Monitoring data from organizations such as Meta, Disney, J.P. Morgan, and KPMG reveal the creation of internal leaderboards that rank employees based on the frequency with which they use the available platforms and models. Julie Sweet, CEO of Accenture, asserts that AI work will become the core operating mode within the firm, noting that promotion is now contingent on adhering to this approach. In contrast, Brian Armstrong, CEO of the cryptocurrency trading platform Coinbase, has laid off engineers who did not complete the mandatory AI training, illustrating executive desire to make technical adoption a strict job-security criterion.

These policies conceal mounting pressures to deliver rapid financial returnsAfter a report from consulting firm McKinsey revealed that 94 percent of companies have yet to realize a tangible, significant return on their AI investments, the mismatch places employees before a complex equation. Duncan Trethewick, a marketing manager at an AI training data company, notes that using the tools to shave two workdays per week is not matched by reduced hours or a rewarding wage increase; instead, the immediate boost in productivity becomes a new minimum that obliges the employee to produce more, effectively contributing to the proof that part of their role can be eliminated. Likewise, Pamela, an executive at a major American consulting firm, observes the emergence of a workforce split into two tiers, where fluency with smart tools outweighs years of professional experience, with long-tenured staff being passed over for practitioners who can operate the tools more quickly even if their practical experience spans only a few years.

The imposed usage metric turns into empty, performative practicesWhen performance metrics are tied to the count of platform interactions rather than output quality, the risk emerges. Camille Miller, an applied AI researcher at Henley Business School, warns that making interaction a primary performance standard pushes workers to log artificial activities and route routine transactions through chatbots without genuine need, merely to boost their standing on digital dashboards, creating more compliant rather than more skilled employees. This farce prompted Amazon to scrap its internal leaderboard after staff began assigning pointless tasks to generative tools to climb the ranks, while Louis von Ahn, CEO of Duolingo, reversed the inclusion of AI usage in performance reviews, affirming that work efficiency is decisive and that using the tool itself adds no value. These moves coincide with legal and advisory warnings about a lack of corporate transparency in explaining automation motives and the emergence of labor disputes over fair wage assessment and intensified workloads.

This shift has direct implications for business environments in the Gulf, Egypt and the Arab East, as major institutions, banks and operational entities pursue accelerated digital transformation and rely on global consulting firms to implement modern efficiency frameworks. If regional managers become fixated on measuring employee activity by the number of queries and inputs through forms, organisations risk wasting their staff’s time on superficial tasks to satisfy digital performance indicators, and marginalising those with cumulative insights who rely on rigorous analysis. Conversely, these developments require professionals and officials in the region to equip themselves with skills in directing agents and generative models as auxiliary tools to increase the final value of work, while avoiding superficial reliance on them merely to demonstrate administrative presence.

I see in the retrenchment experiments of tech companies an early lesson for all corporate departments: artificial intelligence is a means to enhance production quality and speed, and to turn it into an optional item in performance evaluation that often ends up inflating office work rather than achieving real savings. Your step as a manager is to assess the financial and operational impact of the integrated results delivered by the employee, and to leave the freedom to choose tools to their professional judgment, instead of holding them accountable for the number of hours they spend in front of robot interfaces.