Three ways to manage AI's environmental impact
More than 90 percent of companies are increasing their use of artificial intelligence, but only 39 percent of chief information officers feel confident their organization is managing AI's environmental footprint. That's according to a survey of 1,000 CIOs by IT service provider Logicalis.
Nearly three-quarters of respondents expressed concern about "unchecked" AI adoption. Roughly the same proportion lack confidence that energy efficiency is prioritized as their company embraces AI services and infrastructure.
Sustainability leaders have a clear opening to support their company's technology strategists. Here's how.
Request emissions data in contracts and bids
Sustainability teams should apply the same supplier responsibility standards they use with other vendors to those providing AI software. A growing number of clients are seeking emissions data about their AI-related technology, which service providers can calculate by converting electricity usage into a carbon footprint.
Marshall Chase, director of sustainability for Micron Technology, said imperfect information is better than none. "There's enough 'good enough' information out there to take a stab at estimating our AI usage impacts," he said.
Emissions data typically isn't shared widely outside of sustainability teams, but they can establish benchmarks and interpret trends for departments using AI. Include reduction targets in long-term contracts and require prospective suppliers to disclose environmental information as part of the bidding process.
Encourage AI vendors to set reduction targets
Sustainability teams can work alongside corporate procurement to evaluate whether potential AI vendors are willing to manage and reduce their electricity and water consumption. This is especially important for strategic vendors.
John Mennel, U.S. sustainability and cleantech leader at Deloitte, said helping your organization meet emissions reduction commitments could create incentives for better contract terms over time. For second-tier partners, collect this information with an eye to the future.
"You need to be able to pick battles and tell procurement how they should make tradeoffs," Mennel said.
Nudge employees toward less energy-intensive options
Sustainability professionals can win support from technology counterparts by demonstrating how reducing AI-related energy and water consumption translates into cost savings. Decommissioning underutilized servers and consolidating workloads onto more efficient hardware is one effective strategy.
Reducing the volume of data your company stores is also essential, because it lowers the energy required to train algorithms. Boris Gamazaychikov, former AI sustainability manager at Salesforce, said the framing matters: "Explain that the sustainability of AI is not just an environmental concern but that there are other risks that you have in common, including costs."
The amount of energy AI uses depends on where "tokens" - the words and characters used to generate answers or train algorithms - are processed. Companies can control which cloud computing service or data center delivers the work, said Ryan Bogner, digital sustainability leader at EY.
Automation can direct certain types of AI queries based on energy consumption in the background, invisible to employees. "CIOs don't want to tell you not to use the tools, but they are managing on the backend to keep the footprint low," Mennel said.
For more on managing AI in your organization, explore AI for Management or learn about the AI Learning Path for Sustainability Analysts.
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