This article addresses the growing tension between AI adoption in HR and the strategic capability required to translate that adoption into meaningful outcomes. Amy Mosher, Chief People Officer at isolved, argues that the dominant HR metrics — time-to-fill, cost-per-hire, and other efficiency measures — are insufficient predictors of success and that the field must transition from operational to strategic execution. Drawing on isolved's 2026 HR Trends Report, which found that nearly 70% of HR leaders are using AI in some capacity, Mosher distinguishes between tool usage and data interpretation, identifying the latter as the field's most significant skills gap. She also challenges the framing of a 'talent shortage,' attributing it instead to poorly defined role qualifications and an inability to translate attributes such as adaptability and curiosity into AI-driven sourcing models. Isolved's internal approach emphasizes change management as a prerequisite for effective AI implementation, with HR positioned as the function best suited to lead that organizational transition. The article concludes that AI's value is contingent on the interpretive and change management capabilities of the HR professionals deploying it. Key insights: Nearly 70% of HR professionals report using AI in their work, most commonly in payroll and recruitment, yet tool usage does not equate to the ability to interpret data for strategic decision-making. The so-called 'talent crisis' is reframed by Mosher as a qualifications-definition problem — employers have dropped degree requirements without establishing clear skill, experience, and values criteria to replace them. Traditional HR efficiency metrics such as time-to-fill and cost-per-hire do not predict success and are argued to be inadequate measures of HR's strategic contribution in an AI-enabled environment. Practical takeaways: Organizations implementing AI in HR are observed to benefit from pairing technology adoption with formal change management programs, with HR positioned to lead rather than follow that transition. HR professionals at all levels are identified as needing data interpretation skills — the ability to translate people data into predictive behavioral insights — as distinct from simply operating AI tools.