Third-party AI tools are muddying sustainability metrics
The climate impact of AI tools has become an increasingly important conversation at firms
Nearly three-quarters (74%) of executives find measuring generative AI sustainability a challenge due to limited transparency from AI providers, according to research from Capgemini.
A lack of transparency in disclosure and reporting on generative AI’s environmental impact has become a major obstacle to businesses measuring and reporting on sustainability, the report found.
This was the most cited reason execs gave for not measuring the environmental impact of the technology, with other reasons being a lack of awareness in leadership teams (68%) and too great a level of complexity in measuring (64%).
With over three-quarters (78%) utilizing pre-trained generative AI models - and just 4% using internal, proprietary models - businesses are heavily reliant on third-party AI tools and, by extension, the associated climate metrics.
“You should be able to ask Copilot or ChatGPT what the carbon footprint of your last query is but none of the tools will give you a response to that question at the moment,” Niklas Sundberg, CDO at Kuehne+Nagel, said in the report.
Cyril Garcia, Capgemini’s head of global sustainability services and corporate responsibility, suggested these results point to a need for greater collaboration on sustainability.
“If we want generative AI to be a force for sustainable business value, there needs to be a market discussion around data collaboration, drawing up industry-wide standards around how we account for the environmental footprint of AI,” Garcia said.
Sign up today and you will receive a free copy of our Future Focus 2026 report - the leading resource for IT decision-maker insight on priorities and investment areas in AI, security and more.
Almost a third (31%) of those surveyed said they’d taken steps to build sustainability into generative AI lifecycles, while over half are either using smaller models or power infrastructure with renewables - or plan to over the next 12 months.
AI sustainability is a hot topic
As generative AI continues to ramp up power consumption in data centers across the world, several firms are turning their attention towards sustainability in AI development.
RELATED WHITEPAPER
AWS, for example, unveiled new sustainable data center components at the end of 2024, with the firm’s sustainability lead Margaret O’Toole telling ITPro how this forms part of a wider mission at the firm.
Research from SambaNova recently found that 70% of business leaders said they were aware of the significant energy burden created by using AI tools.
Like the Capgemini report, though, another disconnect was revealed - only 13% are monitoring the power consumption of their AI systems, despite 60% acknowledging that energy efficiency will play an important role in future strategic planning.
George Fitzmaurice is a former Staff Writer at ITPro and ChannelPro, with a particular interest in AI regulation, data legislation, and market development. After graduating from the University of Oxford with a degree in English Language and Literature, he undertook an internship at the New Statesman before starting at ITPro. Outside of the office, George is both an aspiring musician and an avid reader.
-
OpenAI says some of its researchers are blowing through $7,000 worth of AI tokens every dayNews OpenAI has revealed that researchers now spend around $600 each day on AI tokens amidst a surge in agentic coding. Some, meanwhile, are using upwards of $7,000 worth of tokens per day.
-
Nvidia in the crosshairs with the Threadripper Halo AI workstationNews The new device boasts 3.4x the total system memory compared to the Nvidia DGX Station, according to AMD
-
“Enterprises are becoming much more rigorous about the economics of AI”: Snowflake wants to help you cut AI costs by choosing the right model for the right taskNews New dynamic model routing capabilities aim to help customers box clever when it comes to their AI model choice
-
Microsoft has joined the growing list of companies cracking down on ‘tokenmaxxing’News The company is updating internal guidance to reduce rising costs
-
‘AI cost management has the same problems that cloud had’: Enterprises are still facing huge AI bills thanks to ‘tokenmaxxing’ – that means FinOps practices are more important than everNews With firms facing surging AI bills, FinOps techniques are more important than ever
-
‘We are now seeing MAI models outperform general-purpose frontier models’: Microsoft CEO Satya Nadella touts in-house models to cut spiralling AI costs – and reduce growing reliance on frontier labsNews The Microsoft chief says pricey frontier models don't have to be used for every task, and its own in-house MAI models could be the key to reducing costs.
-
3 ways to get your data AI-readySponsored Data placement, preparation, and orchestration make or break an AI project – and the Dell AI Data Platform reduces the strain on enterprise IT teams across both storage and the data foundation
-
‘A company should be able to use a model without giving up the knowledge that makes it unique’: Microsoft CEO Satya Nadella says enterprises shouldn’t be sharing so much data with AI providersNews The Microsoft chief warned that corporate data could be at risk thanks to AI models
-
‘What we’re seeing right now is just rapid escalation in AI token spend’: Accenture tells staff to stop using AI for unnecessary tasks amid surging costsNews Accenture has told some staff to roll back the use of AI for basic tasks while the consultancy grapples with surging AI token costs.
-
‘The claims in the suit are false’: Workday hits back amid lawsuit claiming AI recruitment discriminationNews Is AI hiring discriminatory? A California judge has given the go-ahead for a class action suit against Workday