Define the AI PM Standard The Definitive Case for AI-Augmented Program Management and Its Future This is the book that defines the field. While the other editions in this series serve practitioners, leaders, and organizations, this one serves the discipline itself. It provides the theoretical framework, research methodology, and evidence-based predictions that position AI-augmented program management as a legitimate professional practice - not a trend, but a structural transformation in how knowledge work operates. Drawing on complexity theory, sociotechnical systems research, innovation diffusion models, and measured evidence from practice, this edition provides: - A formal theoretical framework grounding the PPP model in established research traditions - The complexity-based argument for differential automation (why some PM work resists algorithmic solution while other work benefits enormously) - Comparative analysis with established frameworks (SAFe, PMBOK 7, Disciplined Agile, Lean PM) - Evidence-based predictions for 2026-2030: adoption curves, capability trajectories, role evolution - Complete research methodology documentation (single-subject design, interrupted time series, limitations) - The professional identity argument: why AI augmentation represents a jurisdictional upgrade, not a displacement Written for thought leaders, researchers, academics, and senior practitioners who shape the field's direction. This isn't a how-to book. It's a what-this-means book.
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