Human Capital Readiness for Artificial Intelligence Adoption: Evidence from Indian Organizational Case Studies

Artificial intelligence is increasingly presented as a transformative technology capable of improving productivity, decision-making, and innovation across sectors. However, many organizations experience difficulty translating experimental AI initiatives into sustained operational outcomes. These challenges frequently arise not from technological limitations but from gaps in organizational capability and human capital readiness. Building upon the Human Capital Audit Framework introduced in the author’s earlier research, this study examines the relationship between human capital governance and artificial intelligence adoption readiness. Through conceptual analysis and illustrative case observations from Indian industry contexts—including manufacturing, retail, and service sectors—the paper proposes a Human Capital AI Readiness Model that identifies key capability dimensions influencing successful AI implementation. The study argues that leadership readiness, workforce adaptability, process maturity, data governance capability, and organizational learning culture collectively determine whether AI initiatives generate meaningful value. Artificial intelligence therefore functions as a stress test for existing human capital governance systems. Organizations with unresolved capability impairments often struggle to scale AI initiatives beyond pilot stages. The paper contributes to the emerging literature on AI adoption by linking technology transformation with human capital governance and proposes a diagnostic perspective for assessing AI readiness in organizations and economies.