Powering the Digital Transformation

Introduction: Status Quo.- From Intelligent Decarbonisation to tofday, the AI era.- AI ¿ compute ¿ data centres ¿ electricity grids ¿ energy security ¿ policy.- Why rising energy use has triggered a backlash 4. Core thesis revisited: AI consumes energy, but delivers net sustainability gains.- Part I: Updating Intelligent Decarbonisation.- Why the optimisation problem has fundamentally changed.- Limits of efficiency-only strategies 3. AI scale-up, rebound effects, and system complexity.- Part II: Data Centres as System Infrastructure.- Data centres as critical energy-system components.- Grid impacts, congestion, and flexibility.- Policy and planning as enabling or constraining forces.- Part III: AI as a Meta-Technology.- AI as a system-wide optimisation layer.- Energy, materials, logistics, and infrastructure planning.- Training and compute aren't consumption but long-term investments.- Already now, AI is assisting humans in solving large-scale problems.- Conclusions: Means to an End, not the End.- AI impact is snowballing, even the next 2 years are unpredictable.- AI impact will challenge governance and require accountability.- Human agency in an AI-optimised world will be critical & governance must support.- Outlook: Further Acceleration & Control.- Technology: AI and Quantum Computing Symbiosis.- Governance: Controlling the Uncontrollable.