When machines learn with organizations: AI ‐enabled knowledge creation and entrepreneurship

Research Summary To promote entrepreneurship and new business development, firms will increasingly rely on new forms of knowledge creation to manage environments marked by technological change and radical uncertainty. We argue that as generative artificial intelligence (Gen‐AI) becomes embedded in organizational processes, knowledge creation will no longer remain solely a human activity. Instead, it will increasingly emerge from hybrid interactions between human actors and firm‐specific, closed Gen‐AI systems. These systems begin to participate directly in how knowledge is generated, recombined, internalized, shared, and converted into entrepreneurial initiatives such as corporate entrepreneurship, spin‐offs, and new business models. We also reconceptualize organizational knowledge creation as a hybrid human–AI process and propose a reordered knowledge creation cycle that induces multiple knowledge spirals, captures the emergence of new agents, and the generation of diverse types of knowledge, with faster temporal dynamics. Building on this perspective, we offer a research agenda for future scholarship. Managerial Summary We discuss how firm‐specific generative AI systems are likely to fundamentally alter the ways firms generate knowledge, respond to change, and sustain long‐term renewal. We propose that rather than replacing human judgment, closed Gen‐AI changes where knowledge originates as well as how quickly it evolves, and how broadly it circulates across organizational boundaries. This means that the managerial challenge is less about adopting AI and more about designing knowledge systems and structuring knowledge flows. Executives and entrepreneurs alike need to decide how to structure human–AI collaborations, how much autonomy to grant closed Gen‐AI systems, and how to prevent speed from overwhelming sensemaking. Our work underscores that although hybrid knowledge creation promises faster and more diverse learning, it also introduces risks related to opacity, trust, and cognitive lock‐in. Firms that deliberately orchestrate the role of closed Gen‐AI in their learning systems will be better positioned to shape future advantage by promoting innovation and entrepreneurial activities of different types.