AI is improving performance measurement. Pay is still human.

The shift, however, isn’t just about efficiency. It also reflects a broader move toward improving the quality and consistency of performance insights. With the ability to surface patterns over time, highlight overlooked achievements, and piece together a more complete picture of employee contributions, AI is helping organizations see performance in ways that were previously fragmented.

That added visibility can also change how employees experience performance itself. Instead of relying on periodic feedback or unclear expectations, more continuous data can make it easier for employees to understand how they’re performing and where they might need to improve.

In fact, Corinne Post, the Fred J. Springer Endowed Chair in Business Leadership and Professor of Management at the Villanova School of Business, pointed to research by an international team that found employees have more confidence in A than in their human managers when it comes to performance assessment. By drawing on larger, more continuous data sets, AI can reduce some of the bias that often shapes performance and pay decisions.

Even so, many organizations are still figuring out how to use that information effectively. While experimentation is widespread, full integration into compensation decisions remains limited.

“There’s an opportunity to call out efficiencies gained with AI, but we don’t want to lose sight of the connection between how work gets done and what’s actually achieved,” Velnoskey said. “We really want performance to still be about outcomes that matter to the organization.”