How We Put Responsible AI Into Practice: The 5 A’s of AI Maturity (Part 1)

Somewhere right now, a data center is asking a utility for more power. AI’s appetite for electricity has become one of the fastest-growing loads on the grid, and it’s showing up on the systems our clients run every day. So, people sometimes ask me a fair question, and it’s one we’ve asked ourselves: why would a company whose purpose is to change our energy future embrace AI?

Here’s where we’ve landed: it’s not growth or sustainability. It’s both. Helping utilities manage new load is exactly what we do. And when we use AI ourselves, we deliver programs faster and at lower cost to the ratepayers who fund them. We see AI as leverage—not a replacement—for our people, and we believe people must ultimately be held accountable for the results. That’s why it’s important to build and follow a framework for responsible usage.

The 5 A’s of AI Maturity

The foundation is awareness. Before anything was ever scaled, we trained our people on what AI is, what it’s good at, and how to use it safely. Next came the climb. Adoption is using off-the-shelf tools like Copilot, where a four-hour task turns into twenty minutes and people become believers. Adaptation is when we started customizing AI for specific business needs, starting with secure pilots on our own data. And acceleration is building our own solutions, like our first AI energy advisor, which led to the agents we run today.

On top of it all is accountability: someone owns the outcomes. For Franklin Energy, that someone is our AI Steering Committee. This makes sure governance and ethics are built in, not bolted on.

When it comes to AI adoption, the first four A’s describe how far you’ve gone. The fifth is what makes it safe to keep going, because without accountability, speed doesn’t scale.

In our next blog post, we’ll break down exactly what accountability looks like in action, including how to ensure your team is AI-ready, establishing safeguards, and keeping humans within the AI interaction loop.

Ready for a one-on-one discussion about how to implement AI responsibility practices into your organization? Let’s continue the conversation.