AI Energy Impact

Sustainable AI for a greener, more affordable, and competitive energy future

Enabling businesses, policy makers, and academia in fostering digital transformation and energy transition through AI. 

In partnership with the Centre for Energy and Materials, and part of the AI Transformation of Industries Initiative, this initiative explores  the energy consumption of AI systems and strategies for managing it, how AI can be sustainably leveraged as an enabler for energy optimization and energy transition, and how to unlock collaboration for scaling solutions through relevant ecosystem enablers. Its vision is to help drive net positive and scalable adoption of AI through collaborative multi-stakeholder engagement.

AI's Global Energy Impact

AI adoption is growing rapidly, and that brings both challenges and opportunities:

TWh dbl. to 945

Energy demand by 2030

10-60%

Energy demands savings est. with AI

50%

Annual growth in electricity use by 2030

$110B

In power plant savings per year by 2035

175 GW

Of transmission capabilities to be released

Policy

Inconsistencies across governments and regions

Objectives

Net Positive Impact

Ensure AI adoption delivers a net positive impact on energy systems by highlighting the business case for AI-driven optimization and energy transition solutions.

AI Energy Efficiency

Improve AI energy efficiency by using the latest innovations and forecasting tools to reduce AI’s energy consumption and guide better decisions.

Regional Energy Goals

Support regional energy goals by unlocking local enablers for AI that strengthen energy ecosystems and enable their transition.

AI Energy Foresight Tool

Your gateway to tested, real-world AI energy use cases from industry peers.

The AI Energy Foresight Tool is a new capability developed to help organizations understand, compare and anticipate the energy implications of AI systems. By providing shared insights and a common analytical base, the tool supports more coordinated decision making, enables responsible scaling and helps stakeholders align AI development with energy system reliability and performance. 

From Paradox to Progress: A Net Positive AI Energy Framework

In collaboration with Accenture and CENMAT, the paper provides a practical blueprint for leaders to ensure AI contributes to energy systems and long term competitiveness.

AI Global Alliance

A World Economic Forum Initiative