Strategic Compensation Series: Paper 3
AI in Compensation
Amplifying Human Judgment, Not Replacing It

AI can analyze compensation data faster than any human. It can surface patterns, flag anomalies, and model scenarios in seconds. It can identify pay equity gaps that might take weeks to find manually. It can process market data and predict retention risks with impressive accuracy.

But should it make the final call on who gets what?

The answer is more nuanced than most AI vendors would have you believe. Compensation decisions involve context that algorithms can't fully grasp, like performance nuances, team dynamics, individual circumstances, and strategic priorities that shift based on factors no dataset can capture.

This paper explores the productive middle ground: how AI amplifies human judgment in strategic compensation without replacing the contextual decision-making that only people can provide. We examine where AI genuinely adds value, where it consistently falls short, and how to design compensation processes that leverage the strengths of both.