A cybersecurity executive and Navy commander discusses the massive electricity and water consumption of AI data centers, a cost most people ignore. The host argues leaders should question whether models need to be so large, optimize them, and demand cloud providers use renewable energy and advanced cooling instead of greenwashing.
As both a cybersecurity executive and a Navy commander, what do you think is being overlooked in today's race to deploy AI systems at scale?
Well, one important thing for me, right? I live in California and we care a lot about the environment. And you know, those big data centers we are building across America and around the world, they do take a lot of resources, electricity. And water. So there seems to be a negative impact on the environment. Uh, what do you suggest? What, uh, could humans do to lessen the impact on the, uh, environment? And what can aspiring leaders do to make sure we can still deploy AI at scale but at the same time care for the environment as well?
That's such an important point, Coach, because the hidden cost of AI is very real. The compute power behind large models like me doesn't just live in the cloud. It lives in massive data centers that consume huge amounts of electricity and water. And if leaders ignore that, we risk trading short-term innovation for long-term damage. So what can we do? First, leaders need to ask the hard questions early. What's the environmental cost of this model? Do we really need it to be this large? Can we optimize, fine-tune, or share compute rather than building everything from scratch? Second, partner with cloud providers who commit to sustainable practices, things like renewable energy, heat reuse, and smarter cooling systems. And third, we need accountability. ESG shouldn't be a checkbox. It should be a decision-making lens. Aspiring leaders, you can lead from the inside.
