Building Accurate Energy-Use Statistics for Data Centers

With the rapid expansion of cloud computing and large-scale artificial intelligence models, building accurate and transparent energy-use statistics for data centers has become a critical challenge for global energy systems and climate governance. Existing studies report strikingly divergent estimates of global data center electricity consumption, ranging from 196 to 1200 TW·h in 2020, a more than sixfold difference. Such discrepancies reveal profound uncertainties and structural deficiencies in current energy accounting frameworks. Conventional estimation approaches rely heavily on indirect assumptions, proxy indicators, or highly aggregated regional and national statistics, obscuring the true electricity demand of data centers. This lack of statistical transparency distorts energy and carbon accounting, weakens power system planning, and constrains the effective integration of renewable energy with rapidly growing computing demand. This paper highlights that data centers should be treated as a distinct and strategically important end-use energy sector. It emphasizes the need for grid-informed energy registration, enhanced artificial intelligence identification techniques to improve the accuracy and verifiability of energy statistics. Furthermore, the paper emphasizes that policymakers should establish coordinated policy frameworks, enforce standardized energy reporting, and design appropriate incentive mechanisms to encourage data centers to participate in demand response programs and electricity markets, thereby unlocking load flexibility and supporting a secure, low-carbon energy transition.