Tracking the Impact of AI: Salesforce’s AI Energy Score

What is the environmental impact of AI?

As AI has risen to global prominence, this question has been brought up repeatedly. The general conclusion is that, due to AI’s reliance on power-hungry data centres, the technology is using large amounts of energy and water making it unsustainable. 

However, as AI continues to develop – and quickly – there emerges a need for more standardised understanding of the specific environmental impact of AI.

Salesforce’s AI Energy Score is a new, groundbreaking tool designed to answer this question – to measure and compare the energy efficiency of AI models.

The AI Energy Score debuts at the AI Action Summit on 10 February 2025, where leaders from over 100 countries, along with private sector and civil society representatives, will convene to discuss harnessing AI for positive impact. Recognised by the French Government and the Paris Peace Forum, this initiative represents a significant step towards more sustainable AI development.

“We are a critical moment with the rapid acceleration of both the climate crisis and the AI innovation," explains Boris Gamazaychikov, Head of Sustainability AI at Salesforce.

"These two trends are interlinked, as we can see exemplified by new gas development slated to support AI data centers. However, there has not been much transparency on the link between AI models and their environmental impacts to date.

"That’s why we created the AI Energy Score - to have a standardised, comparable framework to disclose and compare the impacts of AI. We hope that this remove a key blocker to future where sustainable AI is the norm.”

What is The AI Energy Score?

The AI Energy Score, developed in partnership with Hugging Face, Cohere and Carnegie Mellon University, aims to provide transparency and standardisation in evaluating the energy consumption of AI models.

“The AI Energy Score represents a major milestone for sustainable AI,” says Dr. Sasha Luccioni, AI & Climate Lead, Hugging Face. 

“By creating a transparent rating system, we address a key blocker for reducing the environmental impact of AI. We’re thrilled to launch this project and look forward to seeing wider adoption.”

The AI Energy Score introduces several key features to promote transparency and sustainability in AI development:

• Standardised energy ratings: A framework that evaluates AI models' energy efficiency, requiring developers to measure energy consumption.
• Public leaderboard: A comprehensive ranking of more than 200 models across 10 common AI tasks, including text and image generation.
• Benchmarking portal: A platform for submitting and evaluating both open and proprietary AI models.
• Recognisable energy use label: A 1 to 5-star rating system for easy identification of energy-efficient models.
• Label generator: A tool for AI developers to create and share standardised energy efficiency labels for their models.

The introduction of the AI Energy Score is expected to have far-reaching implications for the AI industry:

• Driving market preference: By enhancing transparency, the score can drive market preference towards more efficient models.
• Incentivising sustainable development: The public nature of the ratings is likely to encourage AI developers to prioritise energy efficiency in their model designs.
• Facilitating informed decisions: AI users and developers can make more informed choices about which models to use or build upon, based on their energy efficiency ratings.

Salesforce's commitment to sustainable AI

Salesforce has positioned itself at the forefront of this initiative by becoming the first AI model developer to disclose energy efficiency data for its proprietary models under the new framework. This commitment aligns with the company's broader sustainability goals and its approach to AI development.

The company's Agentforce platform, introduced in 2024, is designed to deploy autonomous AI agents across various business functions while prioritising energy efficiency.

“The AI Energy Score builds on Salesforce’s Agentforce innovation, the agentic layer of the Salesforce Platform for deploying autonomous AI agents across any business function," explains Boris.

"Agentforce offers tools to build and customise agents, as well as a library of ready-to-use skills for sales, service, marketing, commerce, Tableau, Slack and more.

"We’re already seeing some incredible innovations on how organizations use Agentforce. For example, Good360 connects donated goods with people in need. Each year, six billion pounds of goods go to landfills instead of communities. With Agentforce, Good360 now allocates donations more efficiently, cutting waste, reducing emissions — saving 1,000+ employee hours annually.

"Agentforce is built with sustainability at its core, delivering high performance while minimising environmental impact.

"Unlike DIY AI approaches that require energy-intensive model training for each customer, Agentforce is optimised out-of-the-box, eliminating the need for costly or carbon-heavy training."

“Reducing AI energy consumption lowers operational costs, optimises infrastructure and enhances long-term sustainability and profitability,” explains Suzanne DiBianca, EVP and Chief Impact Officer at Salesforce.

“We are proud to work with industry leaders to build a more transparent AI ecosystem.”

Addressing the AI energy dilemma

This initiative comes at a crucial time, as concerns about AI's energy consumption continue to grow.

A recent Salesforce survey revealed that 65% of sustainability professionals believe their companies need to balance the benefits of AI with its environmental impact. 

With AI-driven data center power usage projected to double by 2026, the AI Energy Score provides a timely solution to help organisations manage this challenge.

"The AI Energy Score benchmarking tool is more than just a energy use metric — it can be a strategic business advantage," Boris says.

"By helping organisations assess and optimise the energy consumption of their AI models, it can contribute to lower operational costs, improved infrastructure efficiency and long-term profitability."

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