From Talent Management to Organizational AI Capability: A Conceptual Framework for AI-Ready Organizations

Artificial intelligence (AI) technology remains a massive investment opportunity for organizations, but there is a big disconnect between those that can sustain a pilot to drive successful outcomes and those whose attempts fail to make the cut. The paper believes that the key difference is not technological, but organizational, and finds the answer in what represents a higher-order capability: Organizational AI Capability (OAIC). We draw inspiration from the resource-based, knowledge-based, dynamic capabilities, human capital, and organizational learning theories to propose a conceptual framework proposing that talent management is an orchestrating organizational capability—the building of the foundation for learning and knowledge upon which AI relies and capability rests. The framework enables a transformation sequence of: talent management that affects organizational learning processes and knowledge sharing ability, OAIC that buildup organizational AI readiness. We then develop 8 propositions respectively capturing the ‘how’ and the ‘how and how not’ of this transformation as well as some ‘how and how far' aspects of it, and we provide an explanation why investing in the AI Technology cannot be a proxy for preparing the organizations for readiness if not accompanied by the capability architecture. First, the paper builds on existing discussion around organizational AI capability literature and extends this line of research by adding strategic HR/HR capabilities literature, specifically by incorporating analyses of the micro foundations of AI.Second, it adds to the growing body of literature on organizational AI capability by adopting a strategic HR/HR capabilities perspective, in that its focus is on the capability of whole organizations to become AI-ready. Theories, management practice, and future empirical studies are discussed.