AI-Native Product Management: A Vision

Abstract:Artificial intelligence is increasingly used to support product management tasks. At the same time, AI-native research and development (R&D) may increase software realization capacity. Organizations may realize software faster than they can identify, qualify, and reconsider what should be realized. This paper asks how product management should be re-envisioned under these conditions. We synthesize research on software product management, product learning, human-AI collaboration, and the Product Management and R&D boundary. We propose a vision in which AI becomes a persistent participant in product work. The vision covers sensing, exploration, decision-making, realization, and learning. We propose six principles and make the vision tangible through an operating model grounded in human professionals, AI personas, agents, skills, and a shared product context. We further argue that AI-native Product Management and AI-native R&D can form a continuous product-learning process. Finally, we identify four AI-specific research directions that require empirical investigation.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

arXiv:2610.14823 [cs.SE]

(or arXiv:2610.14823v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2610.14823 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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