Human-centered strategy in the age of intelligent machines

Abstract This paper develops a human-centered conceptual framework for understanding organizations in the age of artificial intelligence by reassessing organizational capabilities, human agency, and firm-level entrepreneurship. While artificial intelligence is commonly framed as a force of automation and optimization, we argue that its deeper organizational significance lies in the interface it establishes with human intelligence and the restructuring of firm’s human capabilities it generates in the process. Traditional capabilities and strategic human resource frameworks - particularly the static understandings of the resource-based approaches to the firm - prove insufficient for capturing this transformation, as they struggle to account for discovery, the generation of heterogeneity, and processes of change under uncertainty. The paper advances three main theses. First, the diffusion of artificial intelligence underscores and amplifies rather than diminishes the strategic relevance of human judgment, tacit knowledge, and entrepreneurial action within the firm. Second, strategic human resource management emerges as a crucial nexus for analyzing this shift, once the static interpretation of the resource-based view of the firm is transcended. Third, market process theory, rooted in Austrian economics, provides one of the possible dynamic foundations and a solution by integrating entrepreneurship into a theory of the firm and emphasizing knowledge coordination, discovery, and action under uncertainty. The argument unfolds in four steps. We first examine how artificial intelligence compels firms to rethink resources, capabilities, and strategy. We then trace the evolution and limits of strategic human resource management under the resource-based view. Next, we introduce market process theory as a corrective framework. Finally, we articulate a research agenda that integrates strategic human resource management and market process theory to address key organizational challenges at the human–artificial intelligence interface. Together, these elements conceptualize organizations as hybrid systems in which human and artificial intelligence co-evolve within institutionally shaped knowledge processes.