Most teams adopt an AI tool for speed. Very few ask what happens the day that tool changes its price, its rules, or its availability. That question sits at the heart of AI vendor lock-in, and a recent IBM study suggests most organizations are far more exposed than they think.

What AI Vendor Lock-In Really Costs

AI vendor lock-in is the difficulty of moving off a tool once your work depends on it. IBM’s Institute for Business Value surveyed 1,000 senior executives across 16 geographies and 17 industries, and the picture is sobering.

• 71% say switching their primary AI vendor or model would be difficult today.
• Only 9% say they have an excellent understanding of their AI dependencies.
• When a team does try to move, it takes an average of 145 days to shift AI training and operational data to a new environment.

145 days is nearly five months! In a market where models update almost weekly, that is a long time to be stuck with a tool that no longer serves you.

IBM frames the goal as AI sovereignty, which it defines as staying in control when conditions change. The report draws a clean line between relying on AI and depending on it. Relying means the tool helps you work faster. Depending means the work stops the moment the tool does.

The Hidden Side of AI Vendor Lock-In

Most conversations about lock-in race straight to contracts, data, and infrastructure. Those matter. The IBM briefing surfaces a quieter risk that sits much closer to your team: human lock-in.

Your data can be portable while your people are not. Employees fluent in one AI ecosystem often struggle to do the same work in another, even when the data and models are technically movable.

Someone can operate a custom workflow expertly without understanding the thinking behind it. The day the tool changes, that gap becomes painfully visible.

This is the layer most teams skip, and it is the one learning and development is built to close.

AI vendor lock-in is as much a capability question as a procurement one.

A Lesson on Control That Has Lasted 2,000 Years

The story goes that a Roman slave once stood calm while his master twisted his leg for sport. You will break it, the slave warned. The master kept going, and the leg snapped. I told you, was all the slave said.

That man was Epictetus. Born into slavery, lame for life, later exiled from Rome. Almost nothing in his world was his to control. Yet he became one of history’s greatest teachers on freedom, with one enduring idea: some things are within our power, and some are not.

As the son of a teacher, I have always been drawn to people whose lessons outlive them. Epictetus offers the exact frame this moment needs. The vendors, the price hikes, and the outages are not fully within our control. Our judgment, our capability, and our readiness are. Build the part that is yours, because that is the part that lasts.

Continuity: The Driver That Reduces AI Vendor Lock-In

At Radiant Institute we track 7 Drivers of AI Effectiveness. One of them, Continuity, speaks directly to lock-in. It measures how well work keeps flowing when AI tools change, slow down, or fail.

High continuity teams keep a with-AI and a without-AI path for critical work. A model change annoys them for an afternoon. It does not stall a launch. That is what capability looks like in daily practice, and it is the most practical protection against AI vendor lock-in available to any team, whatever its budget.

Ending thought:

The strongest protection against AI vendor lock-in is a team that understands the work beneath the tool. Contracts protect the technology. Capability protects the work. Tools will keep changing their price, their rules, and their availability, and that is fine when your people can adapt without missing a beat.

If you would like help turning this into practice, Radiant Institute designs AI enablement and capability programs that keep your people in control of any tool. Reach out to explore how we can help your team build continuity before the next disruption arrives.