What Leadership Gets Wrong About Deploying AI In Regulated Industries

Olufunsho Peters is the CEO of INFINION Technologies.

Every month, an executive team walks into a boardroom convinced they are six weeks from an AI breakthrough. They have a dazzling demo and the pilot works. Yet, the project stalls the moment it touches a real customer record or transaction.

Technology is not the problem. AI initiatives in regulated industries don’t fail because the models are weak. They fail because executives apply a startup mindset to an environment engineered for the opposite of speed.

RAND research shows that more than 80% of AI projects fail to deliver intended business value because they are treated like software upgrades. Below are the three issues that surface most often, along with a framework called the Governance-First Deployment Model that can help correct course.

1: Treating AI Pilots As Standalone IT Experiments

Leadership will often greenlight a pilot insulated from core operations and regulatory oversight. Of course, it performs beautifully, and often, the success of the pilot makes leadership attempt to scale it overnight.

A model that behaves flawlessly in a sandbox now collides head-on with data privacy statutes or real-time audit requirements in production. That’s when it hits the wall. What looked like a six-week rollout becomes a year of remediation.

Imagine a financial institution that builds a fraud-detection model trained on scrubbed, anonymized historical transactions. It flags fraud impressively in testing. But once wired into live transaction monitoring, the compliance team discovers the model can’t produce an audit trail explaining why it flagged a given customer, something that is a compliance requirement. The launch pauses indefinitely at a greater cost than if compliance had been in the design conversation from the start.

The workaround is to design for production and compliance from day one, not as an afterthought. Risk, legal and compliance leaders belong in the room from the moment of conception, not the approval stage.