ENVENV-003 — Resource Allocation Imbalances
Generative AI Energy and Manufacturing Emissions Lack Consistent Carbon Accounting
3/5Sector: EnergyGeography: GlobalStage: OperateIngested: —
Executive Summary
Large-scale generative AI systems consume substantial energy and carry significant undisclosed manufacturing emissions, yet no consensus methodology exists for calculating their total carbon footprint. Energy firms deploying AI face mounting regulatory and reputational exposure as disclosure requirements tighten and carbon accounting gaps become indefensible.
Domain
Environmental Factors
Blindspots in organisational culture, stakeholder expectations, resource allocation, market pressure, regulatory environment, and external partnerships.
Source
MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023) ↗https://airisk.mit.edu/
Could this happen in your organisation?
A Velinor AI Audit maps your active AI portfolio against the 50+ blindspots and benchmarks against documented sector failures like this one. A board-ready foresight document in 5 weeks.