Your AI strategy has an employee problem

Companies continue to invest billions in their AI transformations, while their workers struggle to use AI effectively. Gartner forecasts AI spending to grow to $2.59 trillion this year, an increase of 47% from 2025. As AI adoption increases, employees have grown more comfortable using the tools to take over their administrative responsibilities, so they have more time to do higher-impact work.

But even as AI is being used more, the actual business results are questionable. A recent study by Domino Data Lab found that the share of enterprises whose ROI fails to outpace their investment has held at 57% since 2025. While organizations understand the importance of equipping their workforces with AI tools, most still fail to manage and support their employees as they use them to generate real business outcomes like growing revenue, lowering operating costs, and enhancing their own productivity.

Employees’ AI confidence outpaces their business results

There’s a gap between employees’ confidence in using AI and an organization’s desired business outcome. WalkMe’s third installment of the AI at Work Pulse survey, which has tracked U.S. workers’ use of AI since 2024, found that while 90% of employees feel confident using AI, half said they’ve spent more time trying to get AI to do a task than the task itself would have taken manually.

The new expectations around work are largely driven by managers who expect AI to create more efficiency. More than half of employees surveyed reported that their manager expects more output in the same amount of time, and 33% say they have pretended to be more skilled at using AI than they are.

It’s not just that managers are pressuring employees to use AI to be more efficient; the entire job market is being driven by AI, which means those employees who have AI skills and can deliver on them will have better employment prospects.

Dice found that AI skills are now listed in 73% of tech job postings, and KPMG discovered that nearly half of companies are willing to pay a 11% to 15% salary premium for AI skills. Even more jaw-dropping is that a PwC survey of 1,000 financial services executives found that 86% believe AI skills training is more important than an MBA for many new hires. All this pressure to master AI has not only caused employees to make poor decisions around usage but also to suffer from burnout. 

Support employees to achieve desired business results

This AI confidence trap can be overcome by companies that put effort into building a digital adoption infrastructure, change management frameworks, or give contextual guidance to enable employees to effectively use AI. 

The WalkMe survey also found that more than half of employees feel their senior leaders are championing a company AI strategy that they don’t fully understand. Leaders are pushing AI onto their workforce without being proficient themselves, and that disconnect is only part of the problem. 

While managers might be tasked with the responsibility of supporting team AI use, they are caught in the same trap as their workers. The survey found that more than a quarter of managers have pretended to know how to use AI in a meeting or presentation.

Senior leaders reported having at least as much confidence as any other group surveyed, with 39% being guilty of championing, approving, or purchasing an AI tool they don’t even know how to use. These same leaders—more than 40% of them—have pretended to understand their company’s AI strategy while communicating to stakeholders such as employees, peers, and even board members.

If the people at the top of an organization don’t understand AI, how can they expect anyone else to? And they’re the ones making the purchasing decisions when it comes to what AI tool their workforce has to use daily.

So, instead of managers and executives taking the reins, the responsibility falls on IT and learning and development. They are both tasked with ensuring that AI is set up so it’s personalized for individual tasks and functions. Unfortunately, neither of those departments is resourced to solve this problem either. Nearly a quarter of employees have had no AI training at all, and 39% report getting conflicting messages about which tools they’re allowed to use. 

Instead of enrolling in more courses, employees desire guidance built into the tools, better integration with the software they’re already working in, and best practices on how someone in their role effectively uses AI. When AI was effective, the survey found that one-third said the reason was that there was guidance available on their screen while working.

While managers own the conversation about business outcomes, someone else has to own the conditions to make those outcomes possible. At most companies, no one has been assigned that responsibility yet.

Being fluent in AI is not enough

Just saying your employees have adopted AI in their workflow isn’t enough anymore. CIOs already have to defend their AI spend, but now they’ll have to explain the business impact of it with hard data. This is why companies need to start uncovering where AI slows down performance and build in support—whether guidance or automation—to empower employees to utilize AI capabilities in ways that drive business outcomes. There is no greater feedback from employees than their lived behavior. It’s not enough to ask people how they feel about the AI tools at their disposal.

Most organizations have deployed AI, but many have failed to link employee use to ROI. It’s not about having the most AI tools or the biggest investment, but rather the right strategy and support system in place. 

Start by measuring how AI is being used by individuals and teams to see where work breaks down or efficiencies are discovered. Then, build the guidance and context into the tools instead of relying on separate training programs. And finally, continue to solicit feedback from managers on how they are engaging with their workers on AI outcomes.