As the use of generative AI rapidly expands, discussions around corporate energy management and sustainability strategy are also beginning to change.
Until now, the central question has often been, “How can we reduce greenhouse gas emissions?” Of course, that question remains important. At the same time, companies are increasingly being asked to consider how the use of AI and digital technologies aligns with their decarbonization targets and broader sustainability policies.
Generative AI and data analysis tools can contribute to greater operational efficiency and more advanced decision-making. However, the data centers and cloud infrastructure that support these technologies consume significant amounts of electricity.
DX (digital transformation) is an important means of improving efficiency. However, it does not necessarily mean that environmental impact will naturally decrease. Companies may need to revisit this assumption as AI becomes more deeply embedded in business activities.
From Reducing Energy to Designing Energy Use
In the past, energy was often managed mainly as a cost to be reduced. However, as generative AI and cloud services become increasingly integrated into corporate activities, the way companies think about energy may also need to change.
Large-scale computing, cloud-based work environments, and continuous data storage and analysis all involve a certain level of electricity consumption. In other words, greater operational efficiency does not always lead to lower energy use. In some cases, AI adoption may create new electricity demand.
This is where collaboration between DX teams and sustainability teams becomes important. When evaluating the impact of AI adoption, companies need to consider not only operational improvements and productivity gains, but also the associated electricity use and CO2 emissions.
Going forward, technology adoption will require more than simply asking which tools to introduce. It will also be important to consider under what kind of environmental impact those technologies are being used.
How Can Companies Capture Emissions That Are Hard to See?
One of the challenges of energy consumption related to generative AI and cloud services is that it can be difficult to grasp from within the company alone. While electricity use in offices and company-owned facilities is relatively easy to understand, the environmental impact of cloud services and external data centers is often less visible.
Greenhouse gas emissions are generally categorized into three scopes:
- Scope 1: Direct emissions from sources owned or controlled by the company
- Scope 2: Indirect emissions from purchased electricity and similar energy use
- Scope 3: Other indirect emissions across the value chain related to the company’s activities
For AI-related cloud use and data center impacts, companies need to consider how to understand emissions that occur outside their direct control.
In the future, system selection and IT investment decisions may need to take a broader view, including:
- Processing performance and usability
- Implementation and operating costs
- Potential impact on electricity consumption and CO2 emissions
- Use of renewable energy
- Environmental considerations related to Scope 2 and Scope 3
Rather than treating DX and decarbonization as opposing priorities, companies may need to design them together. This shift in perspective is becoming increasingly relevant to sustainability strategy in the age of AI.
The Next Level of Disclosure: AI Use That Can Be Explained
Expectations for sustainability disclosure continue to rise. The disclosure standards developed by the ISSB, the International Sustainability Standards Board, also emphasize the importance of explaining how climate-related risks and opportunities are connected to business strategy.
Related article: Beyond Disclosure: Connecting Double Materiality to Management in SSBJ Compliance
What matters is not only the emissions data itself. Companies also need to explain why energy use is changing, which business activities it is connected to, and how it will be managed going forward. Organizing this background information can help create a more coherent explanation.
Generative AI is likely to become an even more fundamental part of corporate activities. That is why the value created by AI and the energy burden behind it need to be considered together as part of management decision-making.
As a first step, companies may want to consider the following questions:
- Do we understand the potential impact of AI and cloud use?
- Are our DX initiatives aligned with our emissions reduction targets?
- Are we able to explain our approach internally in preparation for future disclosure?
Connecting AI-Era Sustainability Strategy with Business
At Neuromagic, we support companies in designing initiatives that connect sustainability with business strategy, based on each company’s specific situation.
Our support includes:
- Organizing the relationship between AI use, DX initiatives, and sustainability goals
- Clarifying key issues to consider when understanding environmental impacts, including Scope 2 and Scope 3 perspectives
- Connecting sustainability goals with business plans and roadmaps
- Organizing disclosure and communication content based on frameworks such as ISSB and GRI
Sustainability initiatives should not be treated only as responses to individual issues. It is important to understand how they connect with the broader business and organization.
If you are at the stage of wanting to organize your current situation or discuss where to begin, please feel free to contact us.
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