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Michael Leifman

Washington, DC

Michael Leifman is an energy strategist with 20+ years in climate risk, modeling, and decarbonization. Former consulting partner, GE strategist, and DOE/EPA analyst, he holds M.S. degrees from Johns Hopkins and Carnegie Mellon, B.A. from Chicago.

Managing Data Center Uncertainty Part V — From Uncertainty to Action: A Five-Mechanism Integrated Framework

Managing Data Center Uncertainty Part V — From Uncertainty to Action: A Five-Mechanism Integrated Framework

AI data center demand uncertainty is a governance failure, not a modeling problem. The article proposes five integrated regulatory tools to force transparency, align incentives, unlock flexibility, avoid overbuild, and protect ratepayers while accelerating decarbonization

Managing Data Center Uncertainty Part IV — Flexibility Is the New Capacity: Unlocking 100 GW Without New Generation

Managing Data Center Uncertainty Part IV — Flexibility Is the New Capacity: Unlocking 100 GW Without New Generation

The U.S. grid has ~100 GW of hidden capacity that data centers could unlock with tiny, well-timed curtailments. With stronger price signals—geometric demand charges and TOU surcharges—flexibility becomes profitable, enabling rapid AI load growth without new generation.

Managing Data Center Uncertainty Part III — The Utilization Paradox: Scarcity and Waste Inside AI Infrastructure

Managing Data Center Uncertainty Part III — The Utilization Paradox: Scarcity and Waste Inside AI Infrastructure

AI’s energy problem isn’t shortage—it’s misalignment. GPU clusters run at just 60–70% utilization due to data bottlenecks, creating hidden flexibility. With minimal peak curtailment, the grid could integrate ~100 GW of new load. Smarter governance—not more power—is the real solution.

Managing Data Center Uncertainty Part II — Phantom Data Centers: How Strategic Opacity Drives Overbuild

Managing Data Center Uncertainty Part II — Phantom Data Centers: How Strategic Opacity Drives Overbuild

AI developers are inflating power demand with phantom data centers—projects that exist on paper but never connect. Utilities build for the illusion, regulators approve the excess, and ratepayers bear the cost. Increased transparency can break the cycle.

Managing Data Center Uncertainty Part I — The Uncertainty Problem

Managing Data Center Uncertainty Part I — The Uncertainty Problem

AI has broken the grid’s forecasting logic. Data-center demand could double—or stall—by 2028. The problem isn’t prediction, it’s governance. Smarter rules, transparent data, and flexible pricing—not overbuild—will determine how well the grid survives the AI era.