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As HR practitioners, we’re excited about AI’s transformative potential across talent management practices. However, as Allan H. Church, James Scrivani, Gina A. Seaton, and Janine Waclawski thoughtfully note in their new article, when using AI-based tools for leadership assessment and selection, it’s essential to look beyond technological novelty and focus on how these tools enhance decision-making validity. One key insight is the importance of prioritizing what assessment tools measure—not just the “bright and shiny” appeal of new technology. This means focusing on underlying measurement models, using multiple methods for a holistic view, and verifying actual capabilities rather than relying on marketing claims. Validity should never be sacrificed for simplicity or a sleek user experience; assessment tools must accurately predict leadership performance within an organization’s specific context. The authors especially caution practitioners to be wary of vendors unwilling to explain the “black box” algorithms behind their tools, as these decisions directly impact people’s careers and carry significant legal and ethical implications. While AI offers powerful opportunities—particularly in automating development follow-through, long seen as assessment’s “Achilles’ heel”—it should augment, not replace, human expertise.
