Everyone is telling you to use AI. Almost no one has shown you how it actually works. That gap is not a minor inconvenience you can skip past. In my research it was the single clearest line between the leaders who adopted new technology and the ones who never did, and the latest data on AI says the exact same thing.
The divide that surprised me
My 2014 doctoral work was a qualitative descriptive multiple-case study built on in-depth interviews with 19 people across adopting and resisting Fortune 500 organizations. I expected the line between the two groups to be budget, or company size, or age. It was none of those. The cleanest divide was whether the leader could explain what the technology even was.
The numbers were stark. When I asked participants what a social business platform meant to them, three of the five resisting leaders and all three resisting employees could not answer the question at all. They opted out, because they did not know. Of the resisting leaders who did attempt an answer, one believed it referred to physical meetings and another thought it meant social media. The adopting leaders, by contrast, could describe the technology, give examples, and talk about how it was used. These were not unintelligent people on the resisting side. They simply had never been brought up to speed, and you cannot commit to something you cannot picture.
Understanding is the gate
The conclusion from that theme was direct, and it is one of the firmest in the study: if a leader does not at least generally understand the technology, adoption will not occur quickly. Understanding is not a nice extra that arrives after adoption. It is the gate that has to open before anything else can happen. A leader who cannot picture what the technology does cannot evaluate it, cannot direct it, cannot set a sensible strategy around it, and cannot lead anyone else toward it.
A decade later, the most credible voices on AI are reaching the identical conclusion. MIT Sloan Management Review argues that AI literacy for sound strategic judgment is now a non-negotiable leadership competency, and that without it, organizations generate pilots and experimentation but never reach enterprise transformation (MIT Sloan Management Review). The pattern my interviews surfaced in 2014 is now the documented bottleneck on the largest technology shift in a generation.
The scale of it shows up in the adoption numbers. McKinsey found that 88 percent of organizations now use AI in at least one function, but only 7 percent have scaled it across the enterprise (McKinsey, 2025). Boston Consulting Group found the same wall: despite nearly every company experimenting with AI, only about a quarter have moved beyond proofs of concept to capture real value (BCG, 2024). That enormous gap between using AI and actually adopting it is, in large part, a literacy gap. Leaders have the tools. What most of them lack is enough understanding to lead with them.
The literacy gap starts at the top
The most pointed version of this finding is about leaders specifically. BCG’s 2025 research found that in the companies lagging on AI, only 8 percent of C-suite leaders are deeply engaged with the technology, compared to nearly all of the leadership in the companies pulling ahead (BCG, 2025). The understanding gap is not mainly on the front line. It is in the corner office, which is exactly what my research found a decade ago: the awareness of the technology came down from the leader, or it did not come at all.
That is the exact spot most leaders occupy with AI today. They have heard the hype, felt the pressure, and maybe opened a chatbot once or twice. What they have not had is anyone to show them how the thing works well enough to make confident decisions with it. The pressure is high and the literacy is low, which is the worst possible combination for adoption. It produces expensive activity with no direction, the pilots that never scale, the tools nobody uses. This is one of the five forces I cover in the 5 drivers of AI adoption, and it is the one most leaders skip straight past on their way to buying something.
Closing the gap
Here is the good news the research also supports. You do not need to become an engineer. The adopting leaders in my study were not technologists. They had enough fluency to understand the system, evaluate it, and direct it, which is exactly how you already lead in every other area of your business without doing every job yourself. You do not write the financial statements to lead finance. You understand them well enough to make decisions. AI is the same. You need enough understanding to evaluate, direct, and trust the technology, and that level is reachable in weeks, not years, especially when someone walks you through it in the context of your own business instead of a generic course.
If you want to know where your understanding actually stands and what to learn first, the Omnine AI Readiness Assessment takes about three minutes. And once you can picture how the technology works, the next question is what to point it at, which is the subject of AI adoption starts with a problem, not a tool.
References
Goodwin, M. R. (2014). A qualitative descriptive multiple-case study: Fortune 500 leaders’ social business platform adoption (Doctoral dissertation, University of Phoenix). ProQuest Dissertations Publishing (UMI No. 3648813).
McKinsey & Company. (2025). The state of AI in 2025: Agents, innovation, and transformation. McKinsey Global Survey on the state of AI.
Boston Consulting Group. (2024). Where’s the value in AI?
Boston Consulting Group. (2025). Are you generating value from AI? The widening gap.
MIT Sloan Management Review. Why AI demands a new breed of leaders.