AI learning is a top priority for both employees and executives, but a widening gap is emerging between investment and real-world impact. While leadership strives to accelerate AI investment, many workers, particularly in frontline and junior positions, still don’t understand how the technology will impact their daily responsibilities or long-term career paths.

In fact, the recent AI Readiness Gap Report from Docebo, a leading AI workforce readiness platform, found that 85% of employees can’t apply their AI training to their daily work, despite AI adoption and fluency ranking as the number one learning priority of learning leaders. "Spending on AI training isn't the same as building capability,” said Alessio Artuffo, CEO of Docebo. “If it doesn't change what people can do in their work, you've spent the budget and built nothing."

According to a recent survey from my company, Prosper Insights & Analytics , over half (54%) of executives and business owners already use AI. For employees, usage is only at a third (33%). This contrast makes it clear that much of the workforce is still waiting to be meaningfully brought along on the AI journey. For many employees, the awareness and intent are there. The gap comes from the disconnect between theoretical training and practical, role-specific application. The AI Readiness Gap report revealed that half of employees have received no training or not enough training to help them understand the use of AI in their roles. "Most training happens in one place, and the work happens in another. That gap is the whole problem,” said Artuffo. “Build the learning into where people already work, and adoption follows."

Another disconnect between learners and leaders also comes from a personalization perspective. Though Docebo’s research showed that nearly four out of five learners say their learning isn’t personalized, less than two-thirds of leaders feel the same way. Further, 56% of learners don’t feel like they have enough time in the day to complete whatever training they do have, personalized or not. Learners’ needs are not being met, and its leadership teams’ responsibility to find a solution to that rift.

Many organizations are struggling to move past AI pilots. The AI Readiness Gap Report showed that over a third of learning leaders say they’re still in the experimental stage when it comes to AI. For those who have moved past the initial phase, the challenge shifts from technical performance to measurable business outcomes. Low workforce adoption is becoming the critical barrier to scaling because technology without buy-in doesn't generate returns. Without broader employee engagement, even high-performing AI tools will stall at the pilot stage.

This problem is compounded by the fact that very few organizations have defined KPIs to measure whether or not AI training is working. Measurement is critical if leaders are trying to prove AI’s ROI. The real metrics that matter include productivity gains, adoption rates, decision quality, and learning-to-application transfer rates. But without accountability structures, AI upskilling risks becoming a check-the-box exercise rather than a driver of real business value.

AI is supposed to absorb the routine and repetitive tasks, which means the skills that remain distinctly human, like clear communication, sound judgment, or creative problem-solving, quickly become the most valuable assets an organization can cultivate. "AI can handle the routine work. It can't decide which work is worth doing. That judgment is what separates the companies that pull ahead from the ones that stall,” Artuffo said. AI tools don't set their own objectives, ask the right questions, or decide what “good” looks like. People do. An employee who can think critically, frame problems precisely, and evaluate results with discernment will consistently outperform one who can’t, regardless of what tools either has access to. In a world where AI makes competent output cheap and abundant, the differentiator becomes the wisdom to know what’s worth doing at all.

The takeaway for organizations: Investing in AI tools without investing in the human skills that govern their use is like trying to wash the windows on the top floor without any scaffolding. Technology evolves rapidly, but people who apply it thoughtfully remain the true competitive advantage.

The AI skills gap isn’t a technology problem. The tools exist. The access is there. What’s missing is the bridge between having AI capabilities and strengthening the organizational muscle to use them well. That is a people and strategy problem that requires a people and strategy solution. Closing that gap demands specificity — identifying which roles interact with AI and how, designing training grounded in real workflows rather than abstract concepts, and defining success in measurable terms. Generic approaches produce generic results.

The organizations that win will be the ones that move fastest from literacy to practice by embedding AI fluency into everyday decisions, processes, and culture. That transition doesn't happen by accident. The companies that make it happen deliberately will be the ones that turn AI investment into lasting competitive advantage.

Disclosure: The consumer sentiment study referenced above was conducted by my company, Prosper Insights & Analytics . This is the same dataset used by the National Retail Federation, and available from Amazon Web Services, Bloomberg, and the London Stock Exchange Group for economic benchmarking.