The AI learning gap: Are business leaders doing enough to educate their teams?

According to a recent MIT report, a remarkable 95% of gen AI programs fail to deliver bottom-line returns. That’s a staggering statistic, given the accelerated pace at which companies of all sizes are scrambling to implement AI in their businesses. These tools are not cheap, and business leaders need to be able to prove value. To get to the heart of the matter, companies must first understand why their AI initiatives aren’t delivering. 

Was it misaligned expectations? Lack of strategy and direction? Adoption just for the sake of it? Let’s face it, FOMO is a real factor. Chasing tech trends is as much of a tripping point when it comes to AI implementation as any tool. Leaders often make impulsive decisions based on hype to demonstrate that they’re an AI-forward company.

When companywide efforts fail, it’s rarely because of one glaring issue, but a combination of more minor snags that, when ignored, balloon into something bigger. In the case of failed AI programs, the culprits vary, but the largest one appears to be a learning gap.

“Some large companies’ pilots and younger startups are really excelling with generative AI,” lead author of the report and a research contributor to project NANDA at MIT, Aditya Challapally, told Yahoo Finance in a recent writeup. Startups led by 19- or 20-year-olds, for example, “have seen revenues jump from zero to $20 million in a year,” he said. “It’s because they pick one pain point, execute well, and partner smartly with companies who use their tools,” he added.

Last year, more than half (54%) of senior leaders said they felt like they were failing amid AI’s rapid growth, per an EY survey of 500 U.S. senior business leaders across industries. “Generative AI’s ‘terrible twos’ have been both volatile and shown incredible promise,” said Whitt Butler, EY Americas Consulting Vice Chair, in a release highlighting the survey’s results. “Leaders are banking on AI as the future but our research uncovered challenges like data infrastructure, which are holding back adoption. Leaders must put emerging and evolving risks like data and change management at the top of their AI transformation agenda to maintain momentum and realize adoption.”

It’s clear that both employers and employees must be equipped to confidently and responsibly navigate the rapidly changing AI landscape.

Companies are grappling with looming talent gaps in machine learning, AI, and generative AI, according to a 2025 Revature survey. The findings note that more than half of leaders said their organizations planned upskilling and training efforts in response to the shortage. But how exactly do you train and upskill your staff when there’s no hard-and-fast AI playbook?

CIOs sit at the fault line of a “growing adaptation gap — the widening distance between the speed of innovation and the enterprise’s capacity to absorb it,” according to CIO magazine. 70% of digital transformations fail to meet their goals, CIO reported.

Successfully integrating AI into your business processes hinges on your employees effectively understanding and utilizing these technologies. And investing in AI training for your employees is critical. Moreover, their AI awareness and skill level should empower them to make recommendations as new and useful tools hit the market.

With new tools surfacing faster than anyone can keep pace with, employees must have a foundational understanding of how to use AI within their work. Don’t overlook your in-house talent. If you already have employees invested in exploring AI’s applications, offer incentives to tap their skills and develop internal training programs.

Layering on AI tools without a plan or a clear understanding of their purpose is a big mistake. Instead of pretending to have all the right answers, business leaders should approach AI upskilling with an open mind (knowing how quickly best practices may shift) and maintain ongoing dialogue with their teams (accepting that their AI expertise is likely limited).

It’s well documented that AI offers unprecedented efficiency and insights. But ultimately, an AI initiative is only as effective as the people supporting it. Organizational and skill-based learning gaps risk undermining successful strategies. By understanding where people and processes lack the necessary skills to implement AI, organizations can transition from AI ambition to real results.

Not sure where to start upskilling your teams for AI readiness?