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Generative AI emerges as sustainability opportunity

Generative AI can be a useful tool for helping business leaders achieve climate and sustainability goals.

Generative AI can help business leaders reach climate goals, particularly when incorporated into a sustainable business strategy.

That's according to Gartner analyst Annette Zimmermann, who spoke on the opportunities and risks of AI for sustainability during the Gartner Tech Growth & Innovation Conference this week. Zimmermann said a sustainable business strategy incorporates environmental, social and governance into decision-making and ties business sustainability goals directly to general business outcomes such as revenue growth. This process includes assessing technologies that can help achieve those goals, such as AI, and weighing the risks and benefits.

Putting business goals together with sustainability objectives can generate much value, Zimmermann said. However, she said business leaders are getting stuck between grand ambitions and achieving sustainability and climate goals, such as reducing carbon emissions. Generative AI presents an opportunity as it can help business leaders achieve climate goals faster.

Clients are telling us they see AI as a crucial technology to achieve climate goals.
Annette ZimmermannAnalyst, Gartner

"Clients are telling us they see AI as a crucial technology to achieve climate goals," she said.

Kenneth Rawlings, product director and vice president of U.S. operations at IoT company Litum, attended Zimmermann's session on generative AI and sustainability. He said as Litum looks to incorporate generative AI into its products, the company is also focused on sustainability goals and creating operational efficiency -- something he said customers are asking for.

"If we can, for example, optimize flows in a hospital or business processes in a warehouse, how can we use AI to not only impact the operational flows, but how can we leverage that to optimize the energy consumed in these operations?" he said.

Sustainability and generative AI

One reason business leaders aren't achieving climate goals is because they're focused on compliance, which does not advance progress swiftly enough, Zimmermann said. California only recently adopted extensive climate risk disclosure rules, while the U.S. Securities and Exchange Commission also finalized requirements for businesses to disclose Scope 1 and Scope 2 carbon emissions.

Instead, Zimmermann said businesses should adopt a "transformative approach" that links business outcomes to sustainability goals. She described this method as a double materiality approach within the sustainable business strategy.

A materiality assessment defines goals that are material to a business, including reshaping a company's social impact or reducing the amount of water used. Businesses then develop a scorecard for this assessment.

Double materiality means assessing those goals from two different perspectives. First, a business's impact from the inside out, such as what activities the company engages in that affect society and the planet overall. The second perspective is from the outside, assessing risks and opportunities that might arise if a company doesn't improve its sustainability performance.

"Double materiality is a two-way street that benefits everyone," she said.

As business leaders look to technologies to help reach sustainability goals, Zimmermann said there have been several use cases where generative AI has proven useful for sustainability. Several emerging carbon management and reporting tools are incorporating generative AI to summarize and create reports automatically, saving time and effort, she said.

Zimmermann pointed to Airbus, an aerospace company, as an example of a company using generative AI for sustainability in its product design and redesign process to develop lighter-weight aircraft parts. The new design is projected to reduce Airbus' annual carbon emissions by nearly 500,000 metric tons if rolled out across its fleet.

However, Zimmermann said the benefits of generative AI need to be carefully balanced against its environmental cost. The training and operational phases of generative AI tools require significant energy, resulting in carbon emissions.

For businesses, incorporating generative AI for sustainability goals should be assessed case by case.

"We should probably not use generative AI for every single task that we could also solve with another technique," she said. "As we've seen, there are some power consumption issues that we still need to solve with generative AI."

Makenzie Holland is a senior news writer covering big tech and federal regulation. Prior to joining TechTarget Editorial, she was a general reporter for the Wilmington StarNews and a crime and education reporter at the Wabash Plain Dealer.

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