Enterprise AI adoption is failing because organizations are teaching employees what AI is, not how to use it wisely. According to Fabio Sacoman, VP of Learning and Development at Expedia Group, the distinction between AI literacy and AI fluency is becoming the defining factor separating companies that successfully transform with artificial intelligence from those that merely check a training box.

What's the Difference Between AI Literacy and AI Fluency?

Most organizations have invested heavily in AI literacy initiatives, helping employees understand foundational concepts about artificial intelligence and how various tools function. But Sacoman argues this is only half the equation.

"AI literacy means foundational understanding in plain language, what AI can do, what AI can't do, limitations, responsible use of AI. But literacy is half of the equation," explained Fabio Sacoman.

Fabio Sacoman, VP of Learning and Development, Expedia Group

AI fluency, by contrast, is the ability to apply AI effectively in real-world situations. It requires judgment, discernment, and practical application. Employees with AI fluency know how to verify outputs, integrate AI into workflows, and critically evaluate where AI should and should not be used. This distinction matters because organizations that succeed with AI transformation will not necessarily be the ones that train the most employees on AI tools; instead, they will be the ones that create workforces capable of applying AI safely, intelligently, and strategically.

Why Tool-Agnostic Learning Strategies Win?

One of the biggest mistakes organizations make is designing learning strategies around specific AI technologies. Sacoman noted that the pace of AI innovation makes this approach obsolete almost immediately.

"In two weeks we can have different tools, completely different tools, more innovative than the ones you have in your portfolio, so it doesn't make sense to do that," stated Fabio Sacoman.

Fabio Sacoman, VP of Learning and Development, Expedia Group

At Expedia Group, this has led to a deliberately "tool agnostic and role agnostic" approach to AI capability building. Rather than focusing on teaching employees one platform or application, the emphasis is on developing adaptable skills and frameworks that can evolve alongside rapidly changing technology. This philosophy also changes how learning roadmaps are built. Instead of creating static 12-month strategies, Expedia Group operates in shorter cycles, running three-month sprints to stay responsive to technological shifts.

How to Embed AI Learning Into Actual Work?

• Integrate into Leadership Conversations: Rather than separating learning from work, embed AI capability building directly into leadership offsites, strategic conversations, and business problem-solving sessions where leaders explore organizational challenges using AI tools and frameworks in real time.
• Focus on Moments That Matter: Target learning interventions at critical business moments when employees are already engaged in decision-making, making the learning immediately practical and highly contextual rather than abstract or compliance-driven.
• Measure Behavioral Change, Not Completion: Move away from traditional metrics like course completions and attendance rates toward indicators tied to behavioral change and operational impact, such as productivity improvements, cycle time reductions, and adoption patterns.

Expedia Group has found significant success with this approach. According to Sacoman, 100% of these embedded learning interventions resulted in at least one participant saying they wanted to extend the experience to their own teams. This highlights an important evolution in enterprise learning strategy: the most effective learning experiences are not happening in isolated classrooms or course portals, but inside live business conversations embedded directly into operational workflows and leadership decision-making.

Why AI Transformation Must Be Business-Led, Not HR-Driven?

Throughout his discussion, Sacoman repeatedly emphasized the importance of strategic alignment. In his view, AI transformation cannot sit solely within HR or Learning and Development. It must be clearly owned and championed by the business itself.

"This AI strategy decision should come from the top. It is something top down, not because it's mandatory, but because it's aligned with the strategy," noted Fabio Sacoman.

Fabio Sacoman, VP of Learning and Development, Expedia Group

At Expedia Group, AI capability building is visibly supported across the executive team, from the CEO through to the CTO. That alignment matters because it affects workforce planning, innovation, customer experience, organizational design, and performance strategy, far more than learning alone. This fundamentally changes the role of L&D professionals. Rather than simply delivering courses or responding to training requests, learning leaders are becoming strategic enablers who influence how businesses think about capability, performance, behavioral change, and future workforce design.

What Metrics Actually Matter for AI ROI?

Traditional learning metrics such as completions and attendance rates are becoming increasingly disconnected from business value. Expedia Group is focusing instead on indicators tied to behavioral change and operational impact. The organization looks at factors such as productivity improvements, cycle time reductions, adoption patterns, time-to-launch for new products, and how employees apply AI capabilities in practice.

Sacoman described a "two-by-two matrix" that measures AI literacy against AI fluency to identify different employee personas and learning needs. This reflects a broader trend emerging across enterprise learning: future learning analytics will increasingly focus on capability application rather than content consumption. For Sacoman and Expedia Group's stakeholders, the most valuable metrics measure adaptability, business impact, and behavioral change rather than simple participation.

How Does This Compare to Other Enterprise AI Leaders?

While Expedia Group is pioneering this fluency-focused approach, other major enterprises are also advancing their AI adoption strategies. A new study from the AI-Driven Enterprise Institute (AIDE) measured how well S&P 500 companies are adopting AI across four dimensions: literacy, advocacy, orientation, and implementation.

The top performers include Nvidia, Amazon, Meta, and Schlumberger, which each scored 100 in the orientation and implementation categories. Walmart followed closely with a score of 95.84, along with utilities companies AES and NextEra Energy. The index drew from publicly available data like earnings call transcripts, job openings, and patent applications to measure how much executives know and say about AI, as well as how much their companies are prioritizing the technology and bringing it into daily operations.

Paul Cheek, CEO of AIDE and a senior lecturer at MIT, emphasized that this data-driven approach helps boards and executives compare their AI strategy to peers without relying on self-reported surveys. "When a board asks a CEO, 'How are we doing compared to our peer group?' I don't want it to be speculative. I want there to be some data that they can use to back up what they have to share," Cheek stated.

Paul Cheek, CEO of AIDE and a senior lecturer at MIT

What Does Leadership in the AI Era Require?

Sacoman emphasized that leadership in this moment requires honesty, courage, and humility. Leaders must be willing to ask uncomfortable questions about changing roles, organizational redesign, evolving workforce expectations, and the reality that many long-standing assumptions about work may no longer apply. He warned leaders against relying too heavily on past success models, arguing that intellectual humility may become one of the defining leadership capabilities of the AI era.

The broader implication is clear: as AI transforms enterprises at scale, the companies that will thrive are those that move beyond checkbox training and build genuine fluency in their workforce. This requires business-led strategy, embedded learning, behavioral measurement, and leadership willing to question past assumptions. For organizations still focused solely on AI literacy initiatives, the window to catch up is narrowing as competitors like Expedia Group, Nvidia, and Amazon advance their fluency-first approaches.