“Measuring and Valuing AI-Enabled Human Capital: Implications for Accounting and Investor Decisions”

The growing integration of artificial intelligence in talent acquisition and retention has introduced significant challenges for conventional accounting systems, particularly in recognizing and measuring intangible value derived from human capital. Although AI-enabled human capital increasingly influences firm performance and investor perceptions, it remains largely underrepresented in traditional financial reporting, creating a notable gap between economic value creation and its formal recognition in accounting records. This study examines the transformative role of AI in converting human capital into measurable intellectual capital and explores the resulting implications for accounting practices and investor decision-making, with the ultimate aim of developing a conceptual framework that captures the value relevance of AI-driven human capital practices.

The research adopts a conceptual and qualitative approach, drawing on established theoretical foundations including value relevance theory, intangible asset measurement, and information asymmetry. Secondary literature and illustrative qualitative insights are employed to identify and analyze key dimensions such as operational efficiency, workforce quality, strategic innovation, ethical concerns, and implementation challenges. The findings reveal that AI-enabled human capital substantially strengthens firm-level indicators, with measurable improvements in operational efficiency ranging from approximately 15 to 25 percent, decision-making speed improving between 20 and 30 percent, and workforce productivity gains of 10 to 20 percent. These outcomes demonstrate a meaningful association with firm valuation metrics and investor confidence.

Taken together, the findings suggest that AI-driven human capital can be systematically translated into quantifiable indicators of intellectual capital, thereby improving the explanatory power of financial information and reducing information asymmetry in capital markets. The study draws attention to a measurable disconnect between value creation and accounting recognition, underscoring the need for refined frameworks capable of capturing AI-enabled intangible assets with greater accuracy and relevance.