Abstract Artificial intelligence workloads are propelling a global wave of hyperscale data-center construction, yet little is known about how carbon intensity and water stress differentials shape sitting decisions or how the resulting externalities intersect with international environmental law. Drawing on a novel dataset of 247 AI-optimized projects announced between 2018 and 2025, this article couples’ event-study econometrics with life-cycle modeling to quantify cross-border spill-overs. Every 100 g CO₂ kWh⁻¹ increase in host-grid intensity raises the probability of attracting new capacity by 8.1 percentage points, while moderate water stress deters investment only when carbon advantages are absent. Median offshore differentials reach 348 kg CO₂ and 0.49 L of freshwater per delivered kilowatt-hour, yielding first-year leakage of 21.4 Mt CO₂ and 1.78 billion L for the sample—volumes that satisfy the “appreciable harm” threshold anchoring the customary duty to prevent significant transboundary damage. Seventy-one percent of these impacts are traceable to companies now covered by the European Union Corporate Sustainability Due Diligence Directive, yet fewer than one in five disclose project-level emissions, and only 7 percent report water use. Scenario analysis showed that 24/7 carbon-free procurement, hybrid cooling, and compute-adjusted border adjustments could halve both carbon and water leakage. The findings expose a latent governance gap but also chart a feasible path toward extraterritorial environmental accountability for cloud infrastructure.Word count: 7,774 words, excluding references.
Usman et al. (Mon,) studied this question.