Financial Services

“In enterprise AI the model is rarely the problem. The system around it almost always is.”

A customer rep promised a discount. It was the right discount. The model said so. The problem — the policy had changed three days earlier. The model didn’t know.

The customer was already engaged. The promise was already made. The rep couldn’t honor it. The customer was furious.

When I was brought in, the team’s instinct was to retrain the model. Expensive. Time-consuming. And in this case — completely wrong diagnosis.

“You’re not choosing whether AI becomes part of your organization. You’re choosing how intentionally and how well.”

Let’s skip the debate about whether AI is coming. It’s already here.

Every organization I speak to is doing AI work in some shape or form. Maybe it’s a pilot. Maybe it’s a vendor tool already deployed. Maybe it’s a team experimenting quietly without a formal program. Maybe it’s all three simultaneously.

“AI tools don’t create value. Organizations that are ready to use them do.”

The biggest AI fear today? Justifying the investment. Yes — fear. Whether you acknowledge it or not.

Every organization is investing in AI. Tools are bought. Pilots are running. Vendors are contracted. And somewhere in every boardroom, every leadership team, every program office — there’s a quiet anxiety nobody is saying out loud. Are we going to be able to justify this?