Podcast: AI Training Gap Scares the Wrong Workers

Here’s the paradox nobody’s talking about in the AI-and-jobs debate. The workers most afraid of being replaced are the ones least likely to be.

Knowledge workers, including analysts, copywriters and coders are squarely in artificial intelligence’s crosshairs. AI models can already draft their memos, crunch their spreadsheets and write their code.

According to new research from PYMNTS Intelligence’s Wage to Wallet collaboration with Ingo Payments and WorkWhile, it’s the roughly 60 million front-line and hourly workers in the Labor Economy who are losing sleep.

Only about 40% of these workers said they believe they could find comparable employment if displaced. Their confidence is, to put it diplomatically, in the basement.

The question is why. Ingo Payments CEO Drew Edwards and WorkWhile CEO Simon Khalaf said on the latest Wage to Wallet podcast with PYMNTS CEO Karen Webster that the answer has less to do with the technology and everything to do with how employers are (and aren’t) communicating about it.

The Training Gap That’s Breeding Fear

The numbers tell a stark story. According to the research, 37% of Labor Economy workers said their employer has already introduced AI or some form of automation into their workplace. However, nearly 60% said they received zero training on those new tools or workflows.

Employers are deploying AI and then not telling workers how to use it. That’s not a technology problem. That’s a management failure.

Only 12% of firms said they are very prepared to manage AI-driven workforce changes. Most chief financial officers identified skill gaps as the primary barrier to adoption, alongside organizational complexity and resistance to change.

Workers are hearing a steady drumbeat of commentary about automation and job loss, and without context from their own employers, they’re filling in the blanks with worst-case scenarios, Edwards said.

“If you’re a worker and what you’re hearing… is that nobody’s going to have a job in five years, that is scary stuff,” he said. “But I don’t think anybody should be naive enough to think that the job you’re doing today is not going to be impacted.”

Demand for Human Labor Is Surging, Not Shrinking

Here’s where the disconnect gets interesting. Khalaf said the picture on the ground doesn’t match the doomsday narrative for front-line workers.

“We are seeing dramatic acceleration in demand for human labor,” he said, adding that utilization across his platform remains consistently high.

The AI being deployed in the Labor Economy isn’t replacing workers; it’s reorganizing how they work. It sits behind job matching, shift assignment and daily task management. It handles the scheduling spreadsheet (or, as Khalaf said, the paper timesheet that still passes for state-of-the-art at many companies). What it doesn’t do is pick up boxes, stock shelves or show up for the shift.

Khalaf offered a telling example from WorkWhile’s own operations. A small team supports tens of thousands of workers through AI-driven systems that provide instructions and manage workflows. The AI didn’t eliminate the workers. It eliminated the middle-management overhead that used to slow them down.

From Doing the Work to Directing It

For workers willing to engage, the shift is less about losing a job and more about gaining a different kind of leverage. Edwards framed it as a move from doing the work to managing the technology that helps do it.

“My experience… is it’s giving me an entirely new team to work with side by side with these people,” he said. “If you know how to give directions, you can build software.”

That’s a provocative claim, but it points to something real. AI tools are lowering the bar for what counts as technical fluency. The premium isn’t on coding or data science. It’s on communication and problem-solving, which are skills that front-line workers already use every day.

Trust remains fragile, however. Asking workers to rely on automated systems for their livelihood, especially in platform-based environments where the decision-making process isn’t transparent, is a big ask, Khalaf said.

Webster suggested that the antidote might simply be experience. When workers use the tools and see tangible outcomes, it stimulates their imaginations. Familiarity breeds comfort, but only if workers get the chance to become familiar in the first place.

The Bottom Line

The Labor Economy doesn’t have an AI problem. It has a communication problem. The technology is making front-line work more efficient, not more obsolete. But when 60% of workers get no training and only 12% of employers are prepared, the vacuum gets filled by fear. And the fear is hitting the wrong people.

“Let’s focus on training,” Khalaf said. “Let’s focus on reskilling our people so that they cannot fear AI. They can embrace AI.”

That’s not a technology roadmap. It’s a leadership one. And the clock is ticking.

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