Your AI Vendor May Not Be Around Next Year. Do You Have an Exit Plan?

Every week another AI tool shows up in your company. A notetaker here, a writing assistant there, a chatbot on the website, a “smart” add-on to your CRM. Most of them were bought on a credit card. Very few came with an exit plan.

That's becoming a real business risk. CIO.com reported that AI companies are closing at a younger age than other startups, and big names are cutting services too. Character.AI filed for bankruptcy in October. OpenAI shut down its Sora API in September. In late October, the AI assistant Ollie announced it is shutting down on November 6, only weeks after raising a $7.5 million seed round.

I've lived through this pattern before. When Broadcom bought VMware, companies that had treated VMware as permanent found out how fast the rules can change. AI is moving faster, and the vendors are younger. If you're signing renewals during budget season, now is the time to plan for the exit.

Why AI Vendor Failure Hurts More Than Other Vendor Failures

When a typical software vendor fails, you lose an application. When an AI vendor fails, you can lose more:

• •Your data. Prompts, outputs, uploaded files and meeting transcripts may be stuck in a format you can't use, or deleted.
• •Your customization. Tuned prompts, trained models and workflows built around one tool's behavior don't move cleanly.
• •Your process. If a team now depends on an AI step, that step stops working the day the service does.
• •Your notice period. Some customers have had less than a week of warning when access was cut.

The AI Tools You Don't Know About Are the Bigger Risk

The tools IT approved are only part of the picture. AI notetakers are a good example. They are now on smartwatches and pendants, not just meeting bots, and CIO.com noted there are still no clear disclosure norms. A class action against Otter.ai alleges meetings were recorded without everyone's consent and used to train models.

For a small or mid-sized company, that raises practical questions:

• •Who is recording client, HR or board conversations?
• •Where are those transcripts stored, and for how long?
• •What happens to them if the vendor shuts down or gets bought?

If you can't answer those questions, you have an AI vendor risk you haven't priced. An AI governance framework doesn't have to be heavy, but it has to cover the tools people actually use.

Five Questions to Ask About Every AI Tool You Depend On

• •Do we own our data, and can we export it in a usable format? Test the export before you sign, not after.
• •What does the contract say about shutdown or acquisition? Look for notice periods, data return and deletion terms, and the right to leave without penalty if the company is sold.
• •Who could replace it? Name a fallback tool or approach for anything that touches customers, revenue or compliance.
• •Who owns it internally? Every AI tool should have a named business owner, not just a credit card holder.
• •Does it meet our security and consent standards? SOC 2, encryption, and clear terms on whether your data trains their models.

Plan for Revalidation, Not Just Migration

Switching AI tools isn't like switching file storage. A new model may give different answers to the same request. Plan for that:

• •Keep a short set of real test cases for each critical AI workflow.
• •Rerun them before switching, and after every major vendor update.
• •Budget time for your team to re-learn and re-check the output.

What to Do Next: A Checklist

• ☐Inventory every AI tool in use: approved, expensed and free.
• ☐Rank them by business impact if they disappeared tomorrow.
• ☐Test data export on your top three.
• ☐Add exit, data-return and change-of-control terms to AI renewals this budget cycle.
• ☐Name a fallback for every critical AI workflow.
• ☐Publish a one-page notetaker and recording policy, including meetings that are never recorded.
• ☐Assign a business owner for each AI tool.
• ☐Review the list every year.

Frequently Asked Questions

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