The 90-Day Test - Your AI vendor is going to disappear.
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The 90-Day Test
Your AI vendor is going to disappear. Here's how to make sure your business doesn't go with it.
By Bill Dunning, founder of Innovations Applied LLC
I run a software company that builds custom integrations for communications technology. Increasingly, that means one thing: wiring AI products into the systems businesses actually run on — bots into phone systems, AI agents into IVR flows, machine-generated answers into customer service queues. I'm the person who has to make the AI vendor's product actually connect to your infrastructure.
Which means I see these products from an angle almost nobody else does: at the seams.
And from the seams, here's what the view looks like:
THE SURPRISE INSIDE
When you buy an AI product for a core business function, three risks come in the box. You paid for one of them.
Layer 1 — The model. The frontier AI provider your vendor is built on. Today's pricing is subsidized by investor capital chasing market share. It can change in a quarter.
Layer 2 — The vendor. The product you actually bought — very often a venture-funded company with thin margins whose business plan is to be acquired. A consolidation wave is coming for this layer. The usual fate of an acquired product: sunset within 24 months. You won't get a price increase. You'll get a 90-day notice.
Layer 3 — You. The business that restructured around the product — reduced the staff, retired the manual process, let the documentation go stale. The layer where the risk actually lands.
You control exactly one of these layers. It's the one most businesses are busy dismantling.
The rest of this piece is about that third layer — how businesses are quietly deleting their own ability to survive the first two, and what it costs to keep it. But first, let me show you the surprise I keep finding inside the box.
Let me tell you about a call I was on recently. A business is putting a conversational AI bot in front of its phone system — the bot handles callers, and hands off to the existing telephony infrastructure when it needs to. Standard automated IVR scenario, exactly the kind of work that fills my calendar now. On the call: me, the client, and the AI vendor's technical representative.
I had ordinary integration questions. How does the bot actually process the interaction? How is the handoff to and from the phone system constructed? What state carries across? Where are the boundaries?
The vendor's own technical rep couldn't answer most of them. Not evasive — genuinely didn't know. It took a full hour of discussion to extract a few fragments of information and a promise to follow up with a data dictionary.
Maybe that was one underprepared person. But here's the thing: it wasn't the first time, and it wasn't the fifth. As more of my work centers on integrating AI tools, this is the pattern — vendors whose products are black boxes even to their own people.
Now sit with what that means for the business on that call. They are about to place a system nobody can fully explain — not them, not me, not the vendor's own representative — directly between their customers and their company. And they're doing it, like everyone is, with a plan to reduce the staff who used to answer those phones.
Which brings me to a question I think every business adopting AI this deeply should be forced to answer:
If that AI vendor sent you a shutdown notice tomorrow — 90 days until the lights go out — could you run your business while you replaced them?
Not "would it hurt." Of course it would hurt. Could you operate? Could you answer your phones at volume? Could you quote, schedule, route, respond? Does anyone left in your company know how those processes work without the tool — when the vendor's own engineers barely know how they work with it?
This isn't an argument against AI
Let's get this out of the way, because anyone raising risk in this conversation gets filed under "Luddite." My company's growth is increasingly built on AI integration work. The capability is real, the demand is real, and abstaining is not a strategy. The businesses deploying these tools well are getting genuine leverage from them.
This is an argument about how you adopt — built around a distinction I've come to believe is the most important idea for any business making these decisions right now:
There is a difference between eliminating labor and eliminating knowledge. Labor elimination is reversible. Knowledge elimination is a one-way door.
When AI takes over work a person used to do, you save the labor cost. That's the number in the vendor's ROI deck. But if the person leaves, the documentation goes stale, and the process now exists only inside the tool — you haven't cut a cost. You've deleted your company's memory of how it does what it does.
You can rehire labor. You cannot rehire memory that has left the building. And what I see from the integration side is businesses deleting theirs one deployment at a time — while connecting to vendors who, as that call demonstrated, may not fully possess the knowledge either.
Why this shakeout will be different from the last one
The comparison everyone reaches for is the dot-com bust, and it's half right. There's a bubble dynamic: enormous capital chasing AI companies, many of them thin wrappers around someone else's model with no durable business. Consolidation is coming. A large share of the AI products being sold today will not exist in five years — acquired, absorbed, or shut down. That part is familiar.
Here's the part that isn't. In 2000, when the dot-coms died, the businesses that had merely bought from them mostly shrugged. Your web design firm folded? You hired another one. The internet was a channel bolted onto the business — not a replacement for its internal organs.
This time the product isn't a channel. It's the process itself. The AI bot isn't sitting next to your call center; increasingly it is your call center. And the ROI case explicitly includes reorganizing around it: fewer people, the tool as the system of record for how the work gets done.
So vendor mortality lands differently. When a SaaS CRM shuts down, you migrate records — painful, survivable. When an AI product that absorbed a business function shuts down, the labor disappears. And if you restructured aggressively, the people who knew how to do it manually walked out a year ago.
Two more structural problems, both of which I watch from the integration seat:
Most businesses carry two layers of someone else's risk. They don't buy AI from the frontier labs; they buy vertical products — AI for contact centers, AI for scheduling, AI for the front desk — built on top of the big models. That's exposure to the model provider's pricing and the app vendor's survival, and the app vendor is very often a venture-funded company with thin margins whose plan is to be acquired. If the model layer raises prices, the vendor eats it or passes it through. If consolidation takes the vendor, you don't get a price increase. You get a sunset email.
The opacity is load-bearing. When I can't get a data dictionary out of a vendor, that's not just my integration problem — it's the customer's exit problem, deferred. Every undocumented handoff, every proprietary interface, every "we'll get back to you on how that works" is a strand in a net that will hold the customer exactly when they most need to move.
The history books about past shakeouts are written by survivors, which is why the popular memory of the dot-com era is "it all worked out." The retrospectives never count the small businesses that bet on the wrong platform and folded quietly. There will be a body count this time too, and it will concentrate among businesses too small to self-host, too restructured to revert, and too dependent on vendors too fragile — and too opaque — to last.
The three kinds of lock-in — and the one that kills
Not all dependency is equal. There are three distinct layers:
Data lock-in. Can you get your information out in a usable format? The oldest form, and the easiest to check: try the export before you need it.
Workflow lock-in. Even with your data out, does anything else speak this tool's language? Integrations, automations, the shape of your team's daily work. This is where I live professionally, and I'll tell you plainly: the difference between a clean migration and a death march is decided at build time, by whether the integration was constructed with documented, standard seams — or fused directly into whatever proprietary interface the vendor offered that quarter.
Knowledge lock-in. The killer, and the one no software audit surfaces, because it's not in the software — it's in your org chart. Does anyone in the company still know how the process works without the tool? Could someone reconstruct your call flows, your routing logic, your service rules from documentation and living human knowledge? Or has "how do we do this?" quietly become "the system handles it" — about a system that, as I keep discovering on vendor calls, even the vendor struggles to explain?
Data lock-in costs money on the way out. Workflow lock-in costs time. Knowledge lock-in can cost the company — because it's the only one you can't fix by spending, and it's invisible until the day you need it.
The insulation playbook
Insulating against this doesn't require abstaining, self-hosting models, or a risk department. It requires treating AI vendors the way experienced operators treat any single point of failure. Seven practices:
1. Run the 90-Day Test on every critical vendor — in writing. For each AI tool touching a core function: if it vanished with 90 days' notice, what breaks, who fixes it, how? If the answer involves a person who no longer works for you, you've found a one-way door you already walked through.
2. Distinguish labor cuts from knowledge cuts — before the reorg. When AI adoption lets you reduce headcount, ask which cut removes effort and which removes the last person who understands the process. Cutting effort is efficiency. Cutting the final knowledge-holder is a bet-the-company decision in an efficiency costume. Sometimes still the right call — but make it consciously, and pay the mitigation cost: documented process capture as a condition of the transition.
3. Make the vendor's engineers explain the seams — before you sign. This one comes straight from my calendar. Put your integrator (or your own technical person) on a call with the vendor's technical staff and ask how the product actually connects: what crosses the boundary, in what format, with what documentation. If their technical representative can't answer, that is your answer. A vendor that can't explain its handoffs while courting you will not become more transparent after you've restructured around them. Demand the data dictionary before the contract, not after.
4. Keep a shadow process for anything mission-critical. Not a parallel manual operation — cost theater no smaller business can afford. Documentation kept current, plus a periodic manual fire drill: once a quarter, route a call the old way, build a quote by hand. A few hours that keep the muscle alive. Think of it like testing your backups — pointless right up until it's everything.
5. Make exportability and standard interfaces purchase criteria with teeth. Full data export, in what format, self-service or by request — and test it during the trial. Prefer tools that connect through documented, standard interfaces even at some feature cost. The premium you pay for portability is an insurance premium, and it's cheap. When the integration is built, insist it be built at the seam, not fused to the vendor's proprietary internals — that decision, made once at build time, is most of your future exit.
6. Underwrite the vendor, not just the product — and negotiate the exit at the entrance. Who funds them? What's their likely path — profitability, acquisition, or death? (The usual fate of an acquired product: sunset within 24 months.) Then get terms while they're hungry for logos: a data-return clause, minimum notice for shutdown or material price changes, month-to-month after year one. This is the best negotiating position you will ever have with them.
7. Cap single-vendor exposure across functions. The all-in-one AI platform that runs your calls and scheduling and customer comms is operationally seductive and strategically radioactive. Two tools with a documented seam between them beat one tool that becomes your entire nervous system.
The upside of being the prepared one
Here's what the doom framing misses. A shakeout doesn't just destroy — it reprices. When consolidation comes, the capability won't disappear; it gets absorbed by survivors and, if history is a guide, gets cheaper. The rails outlasted the railroad bankruptcies. The fiber outlasted WorldCom.
The businesses that come through this well won't be the ones that avoided AI. They'll be the ones that adopted it deeply and kept their memory intact and their seams clean — companies where a vendor's death is a bad quarter and a swap-out project, not an extinction event. Those companies get to shop the fire sale: distressed competitors' customers, suddenly cheap capability, better vendors at better terms.
The window to build that position is now — while your vendors are healthy, the people who know the old ways are still on payroll, export buttons still work, and the vendor's sales engineers still return your calls.
So ask the question. Ninety days. Could you run the business?
If you had to think about it, that's your answer — and your to-do list.
Bill Dunning is the founder of Innovations Applied LLC, a software firm that builds custom integrations for communications technology — increasingly, the connections between AI products and the phone systems, contact centers, and business platforms they're being wired into. Connect with him on LinkedIn.
