Part 4/5 of David Carlin's series on sustainability teams' use of AI today
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In his digest series Ask David, David Carlin explores the challenges sustainability teams face today, giving actionable advice on demonstrating financial value, strengthening business strategy, managing risk, and driving real organizational impact. This new five-part series offers insights into how AI can help bridge the gap between sustainability teams' broad mandates and limited resources. Click to read Part 1, Part 2 and Part 3. In Part 4, David Carlin sheds light on the risks AI poses and how sustainability teams can mitigate them.
The risk side needs much more attention, and I think sustainability leaders have an important role to play.
I was recently discussing this with a board, and one of the points we explored was that oversight of AI is increasingly a sustainability question.
Resource use is one obvious part of that. The International Energy Agency estimates that global data-center electricity consumption could more than double to around 945 TWh by 2030, with AI being the most important driver of that growth. Data-center electricity demand is projected to grow around 15% per year between 2024 and 2030, more than four times faster than electricity consumption across other sectors.
For some companies, AI and data centers could become a significant component of their energy consumption, carbon budget and capital expenditure. Sustainability teams need to be asking what responsible growth in AI actually looks like in that context.
For financial institutions, there is another dimension. The expansion of AI infrastructure creates an enormous financing opportunity, but institutions also need to determine what they are willing to finance and under what conditions.
How do you support data centers that provide economic benefits to local communities without creating excessive pressure on power grids, water resources or other local infrastructure?
We have been working with a bank on exactly these questions, including what policies and practices should govern data-center financing. Institutions understandably do not want to miss the opportunity, but they also do not want to find themselves on the front page of a newspaper because they financed a particularly damaging project.
Then there are the risks associated with everyday AI use: inaccurate outputs, confidentiality, data security, bias, accountability and people becoming overly reliant on technology.
I often compare this moment with the emergence of cyber risk. Connecting companies to the internet created enormous opportunities, but it also opened up an entirely new set of vulnerabilities that organizations had to learn to manage. Companies developed governance, controls, expertise and resilience around those risks.
I think we should approach AI similarly. We should be ambitious about what it can enable while building the governance required to use it responsibly. Sustainability leaders should have a meaningful voice in both sides of that conversation.
For more information, visit the D. A. Carlin & Company or explore David Carlin's Substack.
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investESG
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