Got a call from a CIO last month that started with “our AI vendor just sent a sunset notice.” Three months to migrate off a platform they’d spent 18 months integrating.

This is becoming more common. The AI startup landscape is brutal—funding has tightened, competition is fierce, and many companies that raised big rounds in 2022-2023 are running out of runway.

The Warning Signs Were There

Looking back, there were indicators this particular vendor was struggling. Reduced response times on support tickets. Senior staff leaving without replacement announcements. The product roadmap that stopped getting updates.

But when you’re busy running operations, these signals are easy to miss or explain away.

What Actually Breaks

When an AI vendor shuts down, you lose more than software. You lose:

The model itself. If it’s hosted, it’s gone. If it’s fine-tuned on your data, that investment disappears. Any custom training you did over months or years evaporates.

Integration work. The connectors, APIs, data pipelines you built—all need rebuilding for the replacement platform. One manufacturing client had 23 separate system integrations that all needed rework.

Institutional knowledge. The team that knew the quirks and workarounds leaves with the vendor relationship. Documentation never captures everything.

Momentum. You’ve spent months convincing stakeholders this AI thing works. Now you’re starting over with a new vendor and nobody’s excited anymore.

The Financial Damage

The obvious cost is the sunk investment—licensing, implementation, training. But the real damage is opportunity cost and operational disruption.

A retail client of mine had their demand forecasting AI vendor acquired. The acquiring company pivoted the product within six months. Migration took a year. During that year, forecast accuracy degraded, inventory carrying costs increased, and the CFO lost confidence in technology-led initiatives.

That confidence erosion affected every subsequent project proposal.

Contingency Planning Nobody Does

In theory, enterprises should have vendor continuity plans. In practice, almost nobody does this properly for AI vendors.

Data portability requirements. Your contract should specify how you get your data back—and in what format. “We’ll provide an export” isn’t specific enough. Define the schema, the timeline, the support during transition.

Model portability where possible. If you’ve fine-tuned models on your data, can you take the resulting weights? Usually not, but it’s worth negotiating.

Documentation of the integration architecture. Not just what exists, but why decisions were made. The next team needs context, not just diagrams.

Relationship with alternatives. Keep loose relationships with competing vendors. Not to the point of wasting their time, but enough that you could have a real conversation quickly if needed.

Signs Your Vendor Might Be In Trouble

Some patterns worth watching:

• Leadership changes without clear succession communication
• Pricing changes that seem desperate (deep discounts to close deals)
• Product development slowing despite announced roadmaps
• Customer success team turnover
• News about funding struggles or failed rounds

None of these guarantee failure, but clusters of them warrant attention.

The Acquisition Scenario

Sometimes vendors don’t fail—they get acquired. This can be worse than shutdown because you don’t get a clean break.

The acquiring company keeps the product alive, sort of. Development slows. Integration with the parent company’s platform becomes the priority. Your niche use case becomes deprioritised.

And you’re stuck on a platform that’s technically supported but functionally stagnant.

Building Resilience

The enterprises handling this best are building in resilience from the start.

Modular architecture. AI components should be replaceable. Tight coupling makes you hostage to vendor continuity.

Internal expertise. Don’t fully outsource AI understanding to the vendor. Your team should know enough to evaluate alternatives and manage transitions.

Shorter contract terms. Three-year deals feel safe but lock you in. Annual contracts cost more per year but give you flexibility.

If you’re looking at bringing in external help for AI strategy—whether that’s AI consultants Sydney specialists or Melbourne-based firms—make sure vendor risk assessment is part of the conversation from day one.

The Uncomfortable Truth

AI vendor risk is just part of the landscape right now. The market hasn’t consolidated. Winners and losers haven’t been determined. Some vendors you work with will fail.

The goal isn’t eliminating the risk—that’s impossible if you want to use AI at all. The goal is accepting the risk deliberately and being prepared when it materialises.