Your Next Performance Review May Depend on How You Use AI

At HR platform Gusto, employees are categorized into archetypes ranging from "observers" to "amplifiers" based on their integration of AI into daily workflows. Scott Helmes, the company's chief people officer, notes that this framework aims to standardize coaching conversations rather than enforce rigid quotas. However, the push to quantify AI proficiency has met significant friction elsewhere. Amazon, Uber, and Duolingo have faced backlash or retreated from aggressive tracking, while Meta currently faces a lawsuit alleging that AI-driven performance rankings failed to account for protected medical or parental leave.

Experts warn that the rush to grade AI adoption often ignores the nuances of different job functions. Richard Landers, a professor of industrial-organizational psychology at the University of Minnesota, argues that rewarding AI use without clear goals creates a "false equivalence" that penalizes workers for the sake of metrics. Many organizations currently lack the infrastructure to measure true AI impact, opting instead to track login frequency or volume of output. This has led to a rise in "workslop"—a sprawl of inefficient workflows and security risks born from brute-force adoption.

Progressive firms are attempting to shift the focus from simple usage to qualitative outcomes. At the software company Merge, CEO Shensi Ding prioritizes employees who develop effective automation use cases and mentor their peers. Meanwhile, companies like Travelport are utilizing internal dashboards to provide engineers with granular feedback on code quality. Despite these efforts, a Deloitte report indicates that 84% of companies have yet to fundamentally redesign workflows to match AI capabilities. As a result, many performance reviews remain subjective, leaving employees to navigate a rapidly evolving landscape where the definition of success is still being written.