Since the dawn of time, humans have relied on things they couldn’t easily replace. Fire. The wheel. The one colleague who knows how to fix the printer. And now, according to our latest survey, artificial intelligence. AI has quietly burrowed its way into the heart of how companies operate, like a very efficient tapeworm that also writes your emails.
The question isn’t whether AI is useful. It’s “what happens when the AI you depend on disappears, spikes its prices, or gets acquired by a private equity firm that’s going to strip it for parts?”
Once AI stops being an experiment and becomes the backbone of your business, you’re no longer adopting software. You’re entering a committed relationship with a slightly vague escape clause.
We polled 500 U.S. enterprise executives about AI vendor lock-in, and nearly three-quarters admitted that losing their AI vendor would either disrupt their day-to-day operations or that they’re completely, utterly, catastrophically reliant on it. This report breaks down where that dependency is showing up, why switching is harder than it sounds, and how Zapier can help keep your AI strategy flexible.
Key findings:
47% of enterprises say ending AI services would disrupt key business functions; 27% are completely reliant
When we asked enterprise leaders what would happen if their primary AI vendor’s services ended tomorrow, only 6% said they could stop using it without interruption. Another 20% said they would lose efficiency but keep core functions intact.
For nearly half (47%), the impact would be more serious—at least one key business function would stop working correctly. And over a quarter (27%) say they rely on their AI vendors for most or all of their business operations.
In total, 74% report day-to-day disruption or outright reliance. When one provider underpins how work moves through your business, a pricing change, an outage, or a shift in quality stays contained to a single tool. It ripples into workflows, teams, and customer-facing processes that were built on the assumption that the service would always be there.
That level of reliance changes how teams make decisions going forward. The ones that handle it best tend to plan for flexibility before they need it, not after.
Zapier is specifically designed to help companies reduce reliance on a single AI vendor. By connecting thousands of apps and being flexible with AI models, Zapier lets companies build workflows that can swap, combine, or replace AI models—like GPT, Claude, or Gemini—without re-engineering their entire tech stack.
89% believe they could switch between AI vendors within a month—but those who’ve tried tell a different story
Enterprise leaders express strong confidence in their ability to migrate to a new AI vendor, with nearly 9 in 10 (89%) saying they could do it within four weeks. Many believe it would move even faster—41% estimate 2-5 business days, and 13% say they could complete the switch in a single day. That’s the kind of delusional optimism I usually reserve for thinking I can clean my entire house in the 15 minutes before guests arrive.
Reality is a little less graceful. Two-thirds (66%) have already attempted to migrate between AI platforms. Among those, only 42% report a smooth transition. The remaining 58% say the process either failed outright or required significantly more effort than expected.
By the time migration is on the table, AI has already been woven into internal processes, connected to other systems, and tuned to specific workflows. It has dependencies, edge cases, and little adaptations that nobody documented because they were “temporary.” Swapping the vendor means untangling all of that, which is a different job than simply changing a billing plan.
Switching is possible. It just gets harder when flexibility wasn’t planned for. The deciding factor is often workflow structure, not the model itself. But when AI connects through a neutral automation layer like Zapier, teams can swap models without rebuilding the surrounding system.
Zapier connects thousands of apps across your tech stack, so organizations can swap, combine, or replace AI models while keeping workflows running, rather than treating every migration like a ground-up rebuild.
Nearly half of enterprise leaders cite data migration and dependency as top vendor lock-in concerns
Migration gets complicated fast when your workflows live entirely inside a single vendor’s ecosystem. (It’s almost as if building your entire business on someone else’s proprietary platform might have consequences?) A simple procurement decision morphs into a cross-functional expedition involving security reviews, data mapping, integration rebuilds, and retraining.
That reality shapes how leaders view vendor lock-in. In our survey, 81% say they’re at least a little concerned about their organization’s dependency on specific AI vendors, and nearly a third (29%) say they’re very concerned.
Most of that concern comes down to concentration and portability. Nearly half cite data migration challenges (46%) and overdependence on a single vendor (46%) as primary risks. Close behind are declining service quality (44%), limited flexibility to integrate AI with existing tools (42%), and sudden price hikes (41%). More than a third worry about having a single point of failure (37%) or a vendor going out of business (32%).
The throughline across all of these concerns is control. Teams adopt AI for performance, but they want the ability to change their minds without having to start over.
When asked what vendors could do to reduce lock-in, transparency topped the list. One in three leaders (30%) say clearer pricing, features, and contract terms would make the biggest difference. Another 26% want easier data transfers, and 24% want more flexible pricing.
Enterprises want AI embedded in their operations. They also want optionality, agility, and the ability to change the brain without rebuilding the body.
Zapier, the most connected AI orchestration platform, can help you get over the AI integration gap. With more than 8,000 integrations across the tools you already use, Zapier can bring AI to all your workflows.
47% of enterprises have dedicated internal teams to evaluate and manage AI vendors
Enterprises are getting ahead of lock-in by formalizing their evaluation and management of AI vendors.
Nearly half (47%) now have internal teams dedicated specifically to evaluating and managing AI vendors. Managing AI vendors is a whole job now. Multiple jobs, actually. Entire teams of people whose sole purpose is to figure out which AI tools to use, how to use them, and how to avoid getting trapped in a vendor relationship that feels more like a hostage situation.
That shift shows up in how organizations build their AI stacks. More than 4 in 10 (44%) use multiple AI vendors simultaneously to spread risk across providers. Another 42% maintain contingency plans in case of pricing changes, contract updates, or service outages. So basically, people aren’t putting all their eggs in one basket. They’ve seen what happens when that basket gets dropped, catches on fire, or decides to charge you $50 per egg.
Others are taking technical steps. More than a third incorporate open-source alternatives (35%) or design around data portability and standard APIs (34%). A similar share uses third-party integration or orchestration tools (33%) to coordinate workflows across systems. Some go even further, building proprietary AI tools (31%) or negotiating shorter, more flexible contracts (29%) to maintain leverage.
The common thread is anticipation. Many teams are planning for change before it’s forced on them. They want AI embedded deeply in their workflows, but structured in a way that keeps them adaptable as vendors, pricing, and model capabilities evolve. Because the only thing worse than being stuck with a bad vendor is being stuck with a bad vendor and not having any other options.
Using multiple AI vendors is becoming the default. As models multiply, orchestration plays a bigger role. Zapier can route data and logic between tools and AI models, while consistent AI analytics help teams compare outputs and monitor performance across providers.
AI is mission-critical—but flexibility is the differentiator
AI is already embedded in how teams work. The harder problem now is keeping your options open as vendors change. (And they will change. They’ll change their pricing, their features, their terms of service, their entire business model.)
Zapier connects with thousands of apps across your tech stack, so if you switch AI vendors, your workflows don’t have to start from scratch. And because Zapier is AI model-neutral, teams can swap, compare, or add AI tools without rewriting how their systems connect.
That flexibility fits into a broader AI transformation strategy designed for long-term adaptability. You know, the kind of strategy that doesn’t involve panicking every time your vendor sends an email with “important updates” in the subject line.
Explore Zapier AI and build workflows designed to evolve with your stack.
Methodology
This survey was conducted via Centiment between Jan. 30 and Feb. 6, 2026. Results are based on 542 U.S. C-level executives and decision-makers at organizations that currently pay for one or more AI-related vendors. Only respondents with active paid AI vendor contracts were included to ensure findings reflect real operational and financial commitments. The targeted margin of error is approximately ±4% at a 95% confidence level.
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