AI-Augmented Product Development: A Responsible Methodology for Human-AI Collaboration in Enterprise Product Discovery

AI-driven development methodologies have compressed software construction from weeks to days, but upstream product decisions (what to build, for whom, and why) remain a bottleneck. This paper introduces the AI-driven Product Development Life-cycle (AI-PDLC), a four-phase methodology that positions AI as a collaborative partner in enterprise product discovery while preserving human decision authority at every phase transition. We describe the methodology’s relationship to AI-driven software development (AI-DLC), detail the workshop-based execution model including scoping, facilitation, and tooling, and report on an anonymized enterprise deployment. Initial results suggest 15–25× compression of individual product discovery activities and approximately 20× end-to-end cycle reduction, with participants reporting improved stakeholder alignment. We argue that responsible AI in product development requires methodological design that makes human oversight structural rather than optional.