With the proliferation of AI across industries, organizations will need to reevaluate what type of talent they need and how that talent performs. This will require moving to an evaluation system that is transparently positioned to support learning and adaptation rather than surveillance and control. Here’s how to make such a system work:  

Change what you treat as evidence of capability. What matters here are signals from actual work. Managers can no longer rely on periodic reviews or self-reports to assess performance. Instead, continuously monitor real-time signals, such as customer calls, collaboration patterns, and tool usage, to gauge how your employees are performing. 

Understand when and where AI is used. Which parts of a task were delegated to AI? Which outputs were corrected or revised, and which passed review? Over time, these signals show which tasks AI is absorbing and which employees are learning to supervise and integrate AI-generated work most effectively.  

Turn this insight into action. Use the data you collect to allocate work, develop people, redesign roles, and plan for the future. Rather than waiting for an official training cycle, leaders can take the data from continuous assessment to integrate training into employees’ everyday workflows.

Adapted from When Developing an AI Strategy, Beware the Urgency Trap by David De Cremer

Spread the love