Project Management for AI and Digital Initiatives: An Integrated Practice the Artificial-Intelligence Lifecycle

Artificial intelligence projects combine technical uncertainty with organisational complexity. They require more than conventional project plans, fixed requirements, and one-time delivery. They demand disciplined experimentation, reliable data, production engineering, stakeholder alignment, governance, and continuing attention to value after deployment. Project Management for AI and Digital Initiatives presents an integrated framework for managing this distinctive form of work. It follows the complete AI project lifecycle, beginning with problem framing and feasibility assessment before moving through data preparation, model development, deployment, monitoring, governance, change management, value realisation, and adaptive planning. The book examines the responsibilities of the project director across eleven connected disciplines. It explains how to: - translate business needs into well-defined AI problems; - assess technical, data, organisational, and economic feasibility; - manage data as a governed and evolving project asset; - organise experimentation without losing control of time, cost, or evidence; - bridge the gap between model development and production operation; - design effective AI teams and hybrid organisational structures; - manage sponsors, stakeholders, expectations, and adoption; - establish risk controls, quality gates, and responsible governance; - make informed budgeting, vendor, and make-versus-buy decisions; - select and combine Agile, CRISP-DM, MLOps, and hybrid methods; - plan under uncertainty while maintaining accountability for outcomes. Case studies and practical examples connect the framework to real and illustrative settings across financial services, manufacturing, healthcare, technology, and the public sector. The emphasis remains on decisions, dependencies, and management practices rather than programming. Written for postgraduate students, project managers, programme leaders, consultants, technology professionals, and organisational decision-makers, the book provides a structured guide to turning experimental AI work into governed, operational, and valuable organisational capability.