GenAI Project Management: A Practical Delivery Framework for Enterprise AI Initiatives
This article outlines a practical end-to-end framework for managing enterprise GenAI projects — from requirement gathering to hypercare support. Image: Saklespur | Author: Me :) Generative AI projects are fundamentally different from traditional software implementations. Unlike deterministic systems, GenAI applications rely on probabilistic outputs, evolving datasets, prompt engineering, model orchestration, and continuous monitoring. As a result, project management for GenAI requires a hybrid operating model that combines software engineering, AI governance, data management, and business alignment. 1. Scope & User Requirements The first and most critical activity in a GenAI project is defining the scope clearly. Key Activities: Business Problem Definition Identify: What business challenge is being solved? What productivity gain or automation benefit is expected? Who are the end users? Infra Requirements 2. Features Included & Excluded GenAI projects fail when e...
