Like all knowledge workers, sustainability professionals are trying to navigate the accelerating deployment of artificial intelligence along with its ravenous appetite for energy, water and other critical inputs. Another important question is less considered: What can we not afford to turn over to AI? Where should a human-in-the-loop become a human calling the shots? Here are three instances: Don’t let AI dictate your level of sustainability ambition AI optimizes against the value model it inherits. For most companies, that model is the financials as currently structured — where carbon intensity doesn’t show up in sourcing decisions, water risk isn’t booked as a cost and supply chain fragility is invisible until it becomes a crisis. AI agents trained on that model won’t just overlook sustainability value; they will optimize against the identified business objective to the exclusion of other variables and time horizons. Ask AI to reduce procurement costs, and it will provide a solution for today, without considering supplier performance, impact on Scope 3 emissions or how that supplier shows up in its community. AI is now being used by teams across real estate, capital allocation, manufacturing and product development in exactly this way. Telling AI to “also consider sustainability” is not the solution because instructions get retrained out in the face of optimization. We’ve been talking about the fix for 30 years: embed the value of what’s currently externalized directly into the business model. Someone has to decide what goes into the model before it runs. Embedding sustainability considerations…
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