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


Authors : Ravi Kumar Neelayapalem

Volume/Issue : Volume 11 - 2026, Issue 3 - March


Google Scholar : https://tinyurl.com/2psp3888

Scribd : https://tinyurl.com/mr6thhbx

DOI : https://doi.org/10.38124/ijisrt/26mar902

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : 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.

Keywords : Human Capital Audit, Artificial Intelligence Adoption, Organizational Capability, Workforce Readiness, Digital Transformation, AI Governance.

References :

  1. Becker, G. S. (1964). Human Capital: A Theoretical and Empirical Analysis. University of Chicago Press.
  2. OECD (2019). Skills and Productivity: The Role of Human Capital. OECD Publishing.
  3. World Economic Forum (2020). The Future of Jobs Report.
  4. Ravi Kumar Neelayapalem (2026). A Human Capital Audit Framework: Detecting Capability Impairment in Organizations and Economies. International Journal of Innovative Science and Research Technology.

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.

Keywords : Human Capital Audit, Artificial Intelligence Adoption, Organizational Capability, Workforce Readiness, Digital Transformation, AI Governance.

Paper Submission Last Date
31 - March - 2026

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