Your AI Is Deployed. Your People Are Working Around It.

There's a number in WalkMe's 2026 State of Digital Adoption report that should stop any executive reporting AI progress. 88% of executives are confident their employees have the AI tools they need. Only 21% of employees agree. That 67-point gap, between what leadership believes is happening and what the workforce actually experiences, is where a lot of AI budget quietly leaks.

The report, based on a survey of 3,750 executives and employees across 14 countries, describes a workforce that has quietly decided to route around AI. More than half of workers, 54%, said they bypassed their company's AI tools at least once in the past month and did the work by hand. Only 9% said they trust AI for complex, business-critical decisions, against 61% of executives who do. The tools are deployed and the licenses are paid. People simply aren't using them the way the rollout assumed.

Deployed and paid for is not adopted and trusted

The core confusion here is treating deployment as if it were adoption. A rollout can be "complete" on every dashboard, licenses assigned, tools live, training delivered, while most of the workforce works around it. Adoption isn't whether people have access to the tool. It's whether the work actually runs on it, and by that measure a lot of enterprise AI is a line item without a return.

This is not a story about employees being behind or resistant to change. The trust gap is the tell. When only 9% of workers trust AI for the decisions that matter, that's not a training deficit you can close with a memo. It's a judgment they've formed from using the tools, and it usually reflects a real experience: the AI was dropped on top of how they already work, without fitting the workflow or earning the trust that would make it the obvious choice.

The real cost is time

The same report puts a number on the friction. Workers lose roughly 51 working days a year to friction with the technology they're given, up 42% from 36 days the year before. AI that people route around doesn't shrink that number. It grows it, becoming one more tool to get around. A poorly adopted AI rollout doesn't just miss its promised gain. It taxes the people it was supposed to help, who now work around it on top of everything else.

That's the quiet damage. The budget shows an AI investment. The dashboards show deployment. And the actual effect on the ground is a workforce spending time avoiding a tool the company is paying for.

Adoption is a design problem, not a discipline problem

The reflex when adoption lags is to push harder: more mandates, more training, more reminders. That rarely works, because the problem usually isn't the people. It's that the AI was designed and deployed as a thing to be switched on rather than a thing that fits how work actually gets done. People adopt tools that make their day easier and route around tools that don't, and no amount of encouragement overrides that.

Which means the fix starts with honesty about what's really happening. Measure actual usage, not logins or licenses assigned. Ask employees whether they trust the tool and why they work around it. Then redesign the AI to fit the real workflow, so using it beats avoiding it, because that's the only version of adoption that lasts.

How True Horizon does it

We build AI into the actual workflow and earn the trust that makes it the default, rather than deploying a tool and hoping people take to it. That means designing around how work really gets done and proving the tool beats the workaround where it counts, then measuring real usage rather than vanity adoption. The result is AI your people reach for because it genuinely helps, which is the only kind of adoption that shows up in the results.

What to do now

Before you report AI adoption to your board, measure it honestly. Would your rollout survive an audit of who's actually using it versus who's quietly working around it? If real usage is far below deployed licenses, you don't have an adoption number, you have a leak. Close it by fixing the fit, not by pushing the mandate, because a tool people route around will never become a tool they rely on, no matter how many times you tell them to.

If you want to know whether your AI is genuinely adopted or just deployed, take our AI assessment and we'll measure real usage and show you where the fit is breaking.