Insights from the 2026 Qualtrics EX Trends Report
AI is entering workplaces faster than other technologies before. For some, adoption is going smoothly. For others, the tools are in place but the momentum isn't, and it's not obvious why.
The 2026 Qualtrics EX Trends Report points to why. The problem isn't awareness. It's trust. And that trust is unevenly distributed in ways that most AI rollout plans don't account for.
The divide in your workforce you may not be seeing
Knowledge workers — the people whose roles are most directly exposed to AI — are more optimistic about AI than their frontline colleagues. 53% say they're excited or hopeful about AI changing the nature of their work. Among frontline workers, that figure drops to 40%.
That gap comes from experience.
Frontline workers have seen automation reshape warehouses, logistics operations, and manufacturing floors throughout history. They know what technology can do when it enters the workplace and they see that workers don't always benefit.
Knowledge workers, by contrast, are experiencing AI as something they largely control. They choose what to use, how to use it, and they feel the productivity gains directly. When AI helps you draft faster or make sense of a report in minutes, it's easy to feel like you're on the right side of the change.
Why this matters for your rollout
Enthusiasm among knowledge workers can mask a more serious problem. If your AI rollout is built around the people who are already optimistic, you're designing for half your workforce and leaving the other half feeling like AI is something being done to them rather than for them.
That feeling can manifest. Employees who don't trust that AI was introduced in their interest won't adopt it, even when the tools are technically available and mandated. Over time, disengagement deepens, and the gap between who feels empowered by AI and who feels left behind widens.
The data shows that employees who use AI tools daily or weekly are over 40 percentage points more optimistic than those who use them rarely. The experience itself builds trust.
Listen before you launch
The organizations that close this gap understand their workforce's relationship with AI before they roll anything out, then design the transition around what they find.
That means asking frontline workers specifically: What are you worried about? What would make this feel useful rather than threatening? What has your history with workplace technology taught you?
The answers will vary by industry, by role, and by the particular history of your organization. A care provider's concerns about AI are different from a warehouse worker's, which are different again from a field technician's. Generic reassurance doesn't address specific fears. Listening and understanding does.
Once you know where skepticism lives, you can act on it:
Make the benefit concrete for every role
Frontline workers need to see what AI makes easier, faster, or better for them specifically.
Extend agency to the people closest to the work
The sense of control that shapes knowledge worker optimism can be built into any role. Involving frontline workers in how AI tools are introduced shifts the experience from imposition to co-creation.
Keep listening after launch
Workforce sentiment around AI changes as people gain (or don't gain) experience with it. Measuring that sentiment continuously lets you catch problems early, adjust where tools aren't working, and demonstrate that feedback actually leads to action.
The bottom line
AI adoption is significantly impacted by employee trust. And trust has to be earned.
The EX leaders who get this right will be the ones who understood their workforce's relationship with change before they start, and design for the whole workforce and not just the half that was already on board.
The question isn't whether AI will change your workforce. It's whether your whole workforce comes with you.
