This article is a Statista data page summarizing findings from a 2024 SHRM survey on how HR departments in the United States are using artificial intelligence within performance management processes. The page identifies two anchor findings: that the most prevalent AI use case was assisting managers in providing more comprehensive or actionable feedback to employees, and that the least prevalent use case was identifying potential bias within performance evaluations. However, the specific percentage figures for both findings are obscured behind a paywall, represented by asterisks in the publicly visible text. The underlying data source is attributed to SHRM, published via Statista on June 19, 2025. The page itself functions as a citation reference and data stub rather than a full analytical report. No methodology, sample size, margin of error, or broader breakdown of intermediate use cases is visible in the accessible portion of the content, significantly limiting the interpretive value of the material in its current form. Key insights: The most common AI application in HR performance management in 2024 was supporting managers in generating more comprehensive or actionable employee feedback. Bias detection within performance evaluations was the least adopted AI use case among HR professionals surveyed. The data originates from a SHRM survey of U.S. HR professionals, suggesting practitioner-level adoption patterns rather than experimental or aspirational use cases. Practical takeaways: AI adoption in performance management appears concentrated in feedback augmentation rather than fairness or bias-related functions, indicating a gap between equity-focused AI potential and current HR practice. The low uptake of AI for bias identification in evaluations signals that organizations have not yet prioritized or operationalized this capability, despite ongoing discourse around fairness in performance systems.