No ROI from AI? Time for Some Change Management

Companies across industries are pouring resources into AI adoption, but many aren’t seeing a return on their investment. The problem isn’t that the technology isn’t good enough. It's the people using it.

That's the uncomfortable truth emerging from conversations with AI transformation experts and business leaders alike: The technology is here, but humans are resisting the change.

To understand why so many organizations are struggling to gain meaningful value from AI, I spoke with SmarterX and Marketing AI Institute founder and CEO Paul Roetzer on Episode 189 of The Artificial Intelligence Show.

The Technology Isn't the Obstacle

"The technology is already good enough," says Roetzer. "It is good enough to completely transform your work regardless of what your role is or what industry you are in. If you are not seeing that and the ROI, that is a people problem." 

For knowledge workers especially, we've already crossed into the transformational era. The reasoning models can tackle tasks that were impossible just a year or two ago. So how do you position your organization to capture it?

Three Keys to Gaining Real Value from AI

Jack Soslow, CEO of AI transformation firm Ciridae, crystallized the challenge in a recent post on X. Soslow argues that generating real business value from AI requires three things working together:

1. Business acumen to find the real problem
2. Technical skill to build a solution that works
3. People skills to drive behavior change.

The challenge is that these capabilities rarely exist in one person or even on most teams.

"Technology is the easy part," Soslow wrote. "Finding the problem is harder. But the hardest part, the part almost nobody wants to do, is the human work of driving change. 

“Sitting with people. Earning trust. Refining the product until it fits their hands. Pushing until adoption actually happens."

This isn't a new phenomenon. Anyone who has consulted or led change management in any industry knows: Hand people powerful software without shepherding them through the change, and nothing happens. The tools sit unused. The ROI never materializes.

AI is encountering the same human roadblocks, only the stakes are higher and the timeline is tighter.

The Real Barriers to Adoption

So why aren't more employees embracing AI? The reasons vary, but they almost always come back to humans.

Some people aren't yet convinced AI is important enough to prioritize. Others genuinely fear for their jobs or worry that AI will strip away the work they find meaningful. In many cases, leadership simply hasn't committed, leaving employees with no real motivation to change.

Roetzer sees this dynamic playing out constantly in conversations with organizations of all sizes. Teams filled with talented people who, for various reasons, simply don't want to use AI.

"Either the leaders are the wrong leaders who don't get it and aren't pushing hard enough, or your people within the organization are not understanding the significance and what's gonna happen to their careers,” Roetzer says.

“They're not having a sense of urgency to do it."

The growing problem for those companies and employees resisting change is that competitors who are embracing it are racing ahead. And the distance between the two groups is growing at an alarming rate.

Individuals Can Learn and Grow

Individual workers face fewer barriers to experimentation. There's no change management required when you're only altering your own attitude and habits. That's why you see solo entrepreneurs, programmers, and forward-thinking leaders achieving results that seem impossible to executives stuck in traditional organizational structures.

"I'm more convinced than ever that the AI-forward professionals and leaders, the gap between them and everybody else is going to get so significant, so fast," says Roetzer.

The same dynamic applies at the company level. AI-native startups and AI-forward organizations have a massive advantage right now. This will only increase as AI continues to advance at a rapid pace.  

A Warning for Those Who Don’t Engage

For companies still waiting to go all-in on AI, time is tight. Roetzer predicts this year will be deeply disruptive for organizations that continue to hesitate.

"I don't know how you compete with people who have the knowledge of what these things are capable of and apply them to build their businesses," Roetzer says.

"I just don't get it; how they don’t become obsolete in one to two years?"

It's a stark assessment, but one grounded in lived experience. The capabilities available today, particularly with reasoning models would have been unthinkable just 12 to 24 months ago. And that pace of change isn't slowing.

The solution requires a comprehensive, human-centered approach to transformation: proper education, empathetic change management, and leadership willing to do the hard work of building trust and driving adoption.

Many leaders won't do it. That creates an opportunity for those who will.