Your AI Strategy Has A Hidden Liability; Governance Is How You Find It

Girish Redekar is Co-founder and CEO of Sprinto, building the future of trust for high-growth companies.

​Inside a lot of organizations, AI is starting to look like an old codebase nobody has touched in years.

I’m an engineer first, so that is the comparison I keep coming back to. Nobody did anything obviously wrong. Every commit made sense at the time. But five years later, nobody remembers why half of it is there, and the person who would have to explain it to an auditor has probably left the company.

That’s what’s happening with AI right now, except it’s happening in months, not years.

Adoption usually happens through small, sensible decisions. A business unit picks up a tool, a developer wires an API into a product, and marketing tries a new platform. None of those choices looks especially risky on its own. The problem appears when you add them up over a year and realize nobody has a clear picture of what the organization is actually exposed to.

The Debt Nobody’s Watching Accrue

“Compliance debt” is a good term for this. Compliance debt builds when the business moves faster than compliance can keep up. This can happen with cloud adoption, vendor sprawl or any other change that moves faster than the systems meant to govern it.

Usually, nobody is doing anything wrong. The business is responding to the market, while compliance is often manual, point-in-time and several steps behind what is changing week to week.

AI makes this worse and faster than anything else has.

There’s also a related idea called “trust debt,” the gap between what you tell customers and regulators you do and what you can actually prove. It shows up anywhere claims outrun evidence, and AI is currently one of the fastest places it’s building up. Every system adopted without an owner, documented approval or evidence trail adds to it.