Malaysia Data Center Bubble: Macroeconomic Cycles, Power Constraints, and the Coming AI Turning Point

This paper examines the structural gap between contracted and utilized electricity capacity in Malaysia's data centre sector, drawing on Tenaga Nasional Berhad (TNB) and Suruhanjaya Tenaga (ST) data. As of December 2024, secured capacity across 38 projects totaled 5.9 gigawatts against actual operational load of approximately 405 megawatts — a utilization rate near 7%. The paper separates this verifiable infrastructure finding from a contested macro-cycle framing (Strauss–Howe generational theory, Dalio's Long-Term Debt Cycle) sometimes used to time AI-investment risk to 2026–2028, explicitly grading each claim's evidentiary basis. It documents an active tariff pass-through mechanism already used twice by TNB in under a year and offers regulatory recommendations distinguishing announced, committed, and financed capacity.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-28
DOI
https://doi.org/10.5281/zenodo.21634646
Primary Topic
Asian Industrial and Economic Development
Type
preprint
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preprint

Malaysia Data Center Bubble: Macroeconomic Cycles, Power Constraints, and the Coming AI Turning Point

定一居士 Aodhan煜森
Zenodo (CERN European Organization for Nuclear Research)
Asian Industrial and Economic Development
preprint

Malaysia Data Center Bubble: Macroeconomic Cycles, Power Constraints, and the Coming AI Turning Point

定一居士 Aodhan煜森
preprint en

Abstract

This paper examines the structural gap between contracted and utilized electricity capacity in Malaysia's data centre sector, drawing on Tenaga Nasional Berhad (TNB) and Suruhanjaya Tenaga (ST) data. As of December 2024, secured capacity across 38 projects totaled 5.9 gigawatts against actual operational load of approximately 405 megawatts — a utilization rate near 7%. The paper separates this verifiable infrastructure finding from a contested macro-cycle framing (Strauss–Howe generational theory, Dalio's Long-Term Debt Cycle) sometimes used to time AI-investment risk to 2026–2028, explicitly grading each claim's evidentiary basis. It documents an active tariff pass-through mechanism already used twice by TNB in under a year and offers regulatory recommendations distinguishing announced, committed, and financed capacity.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Asian Industrial and Economic Development
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