Related question
What is AI vendor lock-in, and should we be concerned?
Short answer
Lock-in is when your data, workflows, and integrations become dependent enough on one provider that changing platforms turns into an operational project rather than a purchasing decision. Some dependence is unavoidable. The problem is accumulating it without noticing, which is the normal way it happens.
Every technology decision creates some switching cost. The concern is not commitment. It is commitment that was never actually decided.
The pattern is gradual. Documents connect. Then databases. Then workflows, then automated processes, then security controls, then the way your people work. No single step looks like a strategic commitment. Eighteen months later, moving would mean rebuilding rather than migrating.
One industry leader described the early economics well: the barrier to entry is almost nothing, and if your control system is built entirely inside one provider's toolset you are effectively renting a cage. The speed of the early pilot conceals technical debt that only becomes visible when you try to move the work somewhere else.
There is a newer version of this worth watching. As providers take over more of the surrounding infrastructure, including the stored memory of what your automated systems have been doing, that record ends up inside a proprietary database. At which point you are not just using a model. You are living in the ecosystem, and you have lost your own ability to investigate your own history.
The questions to ask before going deep are straightforward. Can our information be exported in a usable form? Which integrations are proprietary? What happens to our workflows if pricing changes? Could a different provider be substituted without rebuilding everything?
Some technology leaders are handling the current uncertainty by refusing long-term AI contracts outright, on the reasoning that it is genuinely hard to know which providers will still be leading in two years. That is a defensible position right now.