Key Takeaway
As AI adoption grows, concerns about its environmental impact rise, particularly due to increased energy consumption from large language models and machine learning systems. Companies like IBM are addressing these challenges by leveraging AI for sustainability initiatives, such as Kenya’s reforestation program and predictive maintenance technology that reduces emissions. IBM sources 74% of its data center electricity from renewables and has cut operational greenhouse gas emissions significantly ahead of schedule. The company emphasizes partnerships and innovation to tackle climate issues while ensuring ethical AI use, recognizing the collective risks posed by environmental challenges.
As AI adoption and evolution accelerates globally, concerns about its environmental impact have emerged.
While companies are increasingly accustomed to balancing competitive advantages with climate commitments, the rapid evolution of AI has introduced its own sustainability challenges.
A key issue is the rise of large language models (LLMs) and machine learning (ML) systems, which have significantly increased energy consumption in data centers worldwide—prompting technology leaders to seek solutions that enhance performance while lowering carbon emissions.
This challenge coincides with extreme weather events in 2023 that caused over US$150 billion in damage across the US alone, highlighting the urgent need for climate action.
Unlike other sectors, technology companies now face pressure to create solutions that assist multiple industries in addressing climate challenges while also minimizing their environmental footprints.
Corporate leaders like Christina Shim, who has served as IBM’s Chief Sustainability Officer since May 2024, are tasked with navigating these challenges.
IBM deploys AI models to tackle global environmental challenges
With over 310,000 employees across six continents, IBM has substantial potential to drive climate action.
The company has recognized that while AI presents challenges, it can also be part of the solution.
For instance, it is enhancing its environmental initiatives through AI and improvements in data centers with its Granite AI model, an ML system tailored for environmental applications.
One such initiative is Kenya’s national reforestation program, which aims to plant 15 billion trees in regions where forests contribute over one-third of the national GDP through water retention.
This technology empowers agricultural companies to forecast crop yields amid unpredictable weather and assists insurers in evaluating potential fire and flood risks through advanced data analysis.
“This is an incredibly exciting time to lead IBM’s sustainability strategy,” Christina states.
“There is much work ahead in the sustainability arena, but I am excited to tackle this critical issue here.”
In Denmark, IBM’s predictive maintenance technology has extended the lifespan of the Great Belt bridge and tunnel project by 100 years, preventing 750,000 tonnes of carbon dioxide emissions by avoiding reconstruction.
Partnerships drive innovation in sustainable technology
The company collaborates with public, private, and non-profit sectors to develop environmental solutions, acting as “client zero” for new technologies by testing and refining solutions prior to market deployment.
“In a rapidly evolving sustainability landscape, IBM is ideally positioned to pursue partnerships, drive innovation, and deploy technology to accelerate progress,” Christina remarks.
Operating in 150 countries, the company boasts “a century of experience in research, innovation, and community engagement,” she adds, leveraging its research capabilities and community involvement to tackle environmental challenges, including advancements in material science and quantum computing.
Christina emphasizes: “IBM is already contributing through our AI and energy efficiency initiatives, materials science innovations, and thought leadership in quantum commercial development, among other areas.
“There is ample opportunity to enhance our efforts, as well as to integrate sustainability more deeply into our enterprise operations and product development.”
Energy efficiency drives data centre improvements
IBM sources 74% of its data center electricity from renewable sources, with 28 facilities operating entirely on renewable power.
Moreover, its sustainability software has minimized excess computing capacity in AI workloads, reducing energy consumption without compromising performance.
By avoiding 256,000 megawatt hours of energy use, IBM has also launched over 2,100 conservation projects.
In 2023, it successfully achieved its goal of reducing operational greenhouse gas emissions by 65% compared to 2010 levels, two years ahead of schedule.
“Our legacy includes leading the charge in establishing environmental policies long before many companies, helping to develop international standards, and striving for ambitious environmental goals in alignment with the UN IPCC,” Christina states.
How AI optimisation reduces environmental impact
A significant contributor to AI’s carbon footprint is the chips that power it, prompting IBM’s researchers to create AI chip designs that consume 14 times less energy than previous models.
In August 2024, the company unveiled new processors for running AI applications on mainframe computers, and this optimization extends to the company’s foundational models.
For example, IBM offers Granite in various sizes and employs optimization techniques to minimize energy consumption during both development and deployment.
“Our purpose-built AI models like Granite are assisting leaders in understanding and responding to environmental changes,” Christina explains.
“This can help agricultural companies forecast crop yields in increasingly unpredictable weather or enable insurers to better assess potential fire or flood risks.
An example is the Government of Kenya utilizing IBM’s geospatial foundation model to combat deforestation and plant 15 billion trees—a vital initiative in a country where forested areas retain water and support over a third of the national GDP.”
These initiatives arise as extreme weather in the US has disrupted supply chains and insurance markets—Christina notes that this reflects a growing awareness of operational risks: “These challenges present an opportunity, as businesses, governments, and society increasingly recognize that our operational methods face significant, collective risks that must be addressed.”
Tech infrastructure improvements target emissions reduction
Technical infrastructure is a critical component in achieving corporate AI sustainability initiatives.
“There is no shortage of sustainability challenges today,” Christina remarks.
“Yet these challenges also reflect an opportunity, as businesses, governments, and society are becoming more aware that our operational methods face substantial, collective risks that need addressing.”
Throughout all of IBM’s AI sustainability efforts, the company incorporates AI ethics into every use case that its technology addresses.
IBM believes it can collaboratively tackle these issues with AI, optimizing models and infrastructure.
“As a leader in AI for business, IBM understands the critical importance of developing and utilizing these technologies in a sustainable and ethical manner,” Christina concludes.
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