{"id":13882,"date":"2026-06-10T17:13:20","date_gmt":"2026-06-10T11:43:20","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=13882"},"modified":"2026-06-10T17:13:22","modified_gmt":"2026-06-10T11:43:22","slug":"ai-model-cards-environmental-metrics","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/in\/news\/stories\/ai-model-cards-environmental-metrics\/","title":{"rendered":"Measuring AI\u2019s Environmental Impact: How We\u2019re Operationalizing Transparency Through Model Cards"},"content":{"rendered":"\n

Today, Salesforce is expanding its AI model cards<\/a> with standardized environmental impact metrics. This update helps customers better understand the energy consumption and carbon emissions associated with AI models across their lifecycle. Since the era of predictive AI, Salesforce has published model cards to give customers a trusted reference for how each model works, documenting its intended use cases, evaluation results, and guardrails. By adding sustainability data, Salesforce reinforces its commitment to its trusted AI principles<\/a> and ISO 42001-certified<\/a> governance standards. <\/p>\n\n\n\n

The Environmental Challenge of AI<\/h2>\n\n\n\n

AI<\/a> systems rely on significant physical infrastructure, including data centers that consume energy and contribute to carbon emissions<\/a>. As AI adoption accelerates, training and operating models can require substantial computational resources, intensifying the focus on AI\u2019s environmental footprint.\u00a0<\/p>\n\n\n\n

\u201cAs AI adoption accelerates, transparency can\u2019t stop at model performance alone,\u201d said Orlando Lugo, Senior Product Manager, Responsible AI. \u201cOrganizations increasingly want visibility into how AI systems are built and operated, including their environmental impact. By integrating these metrics into model cards, we\u2019re helping make sustainability a more measurable part of trusted AI.\u201d<\/p>\n\n\n\n

At Salesforce, we believe this moment calls for greater clarity, and we\u2019re taking steps to strengthen our own transparency efforts.<\/p>\n\n\n\n

Empowering Our Customers Through Transparency<\/h2>\n\n\n\n

Since 2020, Salesforce has been committed to providing transparency<\/a> through model cards<\/a>: \u201cnutrition labels\u201d for AI models that document information such as usage guidelines, performance data, and potential risks. The new Environmental Impact section is now available for select Salesforce models, including First Name Match, Account Match, and TextEval. <\/p>\n\n\n\n

These disclosures estimate energy consumption and carbon emissions across pre-training, post-training, and inference. To calculate these figures, Salesforce uses the AI Energy Score<\/a> methodology, an emerging industry framework the company helped develop. This framework standardizes AI energy reporting by analyzing hardware type, GPU utilization, runtime, and data center region.<\/p>\n\n\n

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Example of a filled-out Environmental Impact section in one of our model cards, TextEval.<\/em><\/figcaption><\/figure>\n
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