Part 5/5 of David Carlin's series on sustainability teams' use of AI today
Photo credit: Getty Images / Unsplash+
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, Part 3 and Part 4. The last Part of the series develops a concrete action plan on how to incorporate AI into the work of sustainability teams.
We are doing a lot of this work with sustainability leaders now, helping them determine what their AI strategy should look like over the next 12 months, where the strongest use cases are, where they may need support and which opportunities are actually worth pursuing.
This stuff can become complicated very quickly. There are potential efficiency gains, but there are also risks, implementation challenges and costs. The fact that AI can do something does not automatically make it a good use case.
We typically suggest three steps.
First, define the problem. What exactly are you trying to improve? What process is taking too long, costing too much or producing an inadequate result? Start with the problem you are trying to solve.
Second, assess the case for AI. We often look at a best case, average case and worst case for a particular use case. What is the potential upside? Can you quantify the hours saved, costs reduced, quality improved or additional capacity created? Equally, what could go wrong? What errors, governance issues, costs or other risks could be introduced?
Third, work out how you would actually implement it. Who is affected? Where does human review sit? What data and systems are required? What controls need to be put in place? And what does the step-by-step implementation plan look like?
My advice is usually to pick your top two or three use cases and work through them properly.
We already know that the potential applications of AI are vast. Sustainability leaders now need to get practical. Where can AI genuinely create value for your organization? Is the benefit large enough to justify moving ahead? And how can you implement it in a controlled, measurable and useful way?
For sustainability teams in particular, I think the opportunity is significant. AI can reduce the amount of time spent on repetitive processes and create more capacity for the judgment, creativity and systems thinking that organizations increasingly need from sustainability leaders.
Realizing that opportunity requires being deliberate about where AI is used, what you expect from it, and where human expertise remains essential.
For more information, visit the D. A. Carlin & Company or explore David Carlin's Substack.
Published by
investESG
investESG
