AI Energy Score: Salesforce Seeks to Track its AI Impact
As AI continues to rise to prominence, it is becoming more of a sustainable challenge. Particularly as it demands large amounts of power, energy and water, data centres are feeling the strain.
As the technology continues to develop, industry leaders are calling for a more standardised understanding of how AI will continue to impact the environment.
With this in mind, Salesforce’s new AI Energy Score is an industry-leading tool designed to measure and compare the energy efficiency of AI models.
The company unveiled this tool at the AI Action Summit on 10th February 2025, explaining it had developed it in partnership with leading AI companies Hugging Face and Cohere and Carnegie Mellon University.
It aims to standardise the measurement of the energy efficiency of AI models.
“We are at a critical moment with the rapid acceleration of both the climate crisis and AI innovation,” shares 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 centres. However, there has not been much transparency on the link between AI models and their environmental impacts to date.”
AI Energy Score: Explained
The AI Energy Score introduces a framework for evaluating and comparing the energy consumption of AI models. It includes a public leaderboard ranking over 200 models across 10 common AI tasks, a benchmarking portal for submitting models and a 1 to 5-star rating system for easy identification of energy-efficient models.
“The AI Energy Score represents a major milestone for sustainable AI,” explains Dr Sasha Luccioni, AI & Climate Lead at Hugging Face.
- 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 drive market preference towards more efficient models and incentivise sustainable development in the AI industry. It aims to enable AI users and developers to make more informed decisions about which models to use or build upon, based on their energy efficiency ratings.
Dr Sasha Luccioni adds: “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.”
Salesforce: Setting an example
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.
Such a commitment allows the company to align the initiative with its broader sustainability goals and its approach to AI development.
Likewise, the company's Agentforce platform, first introduced in 2024, deploys autonomous AI agents across various business functions while prioritising energy efficiency.
The platform is built with sustainability at its core and seeks to deliver a high performance, whilst minimising environmental impact.
Boris explains: “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.”
The AI Energy Score has come at a pivotal time for the technology industry, as concerns about AI energy consumption continue to mount. In fact, 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 centre power usage projected to double by 2026, the AI Energy Score could provide a timely solution to help organisations manage this challenge, perhaps helping operators track and manage their energy use.
“Reducing AI energy consumption lowers operational costs, optimises infrastructure and enhances long-term sustainability and profitability,” says Suzanne DiBianca, EVP and Chief Impact Officer at Salesforce. “We are proud to work with industry leaders to build a more transparent AI ecosystem."
Boris adds: “The AI Energy Score benchmarking tool is more than just an energy use metric — it can be a strategic business advantage.
“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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