For many organizations, planned or not, the AI era is already well underway.
Budgets are being committed. Tools are being implemented. And teams are being encouraged to experiment. On the surface, progress looks real. But beneath the surface, a quieter reality is taking shape.
While leaders are moving quickly to adopt AI, they’re moving far more slowly when it comes to leading with it.
The gap between adoption and impact
Recent research from LHH brands, General Assembly and EZRA, surveying more than 500 senior leaders across the US and UK reveals a striking contradiction.
On one hand, 93% of leaders say they actively encourage their teams to use AI, and 82% report regular usage. Adoption is no longer the barrier it once was. On the other, the way AI is actually being used tells a different story.
Most leaders are applying AI to surface-level tasks—searching for information (69%), summarizing content (68%), drafting emails (58%). These are useful efficiencies, but they don’t fundamentally change how organizations operate.
Meanwhile, fewer than a third are using AI for more strategic applications like scenario planning (27%), organizational design (27%), or financial modeling (28%).
This is the gap that matters. Not whether AI is being used—but whether it’s being used in ways that drive meaningful transformation.
Why the real challenge is leadership, not technology
It’s tempting to frame this as a workforce issue. A need for more technical skills, more tools, more experimentation. But the data points elsewhere. The most consistent breakdown in AI capability isn’t at the edges of the organization—it’s in the middle.
Vice presidents, the leaders responsible for translating strategy into execution, are falling behind. Only 55% have participated in leadership-specific AI training in the past year, compared to 80% of directors. And just 58% feel confident using AI without compromising company data.
This matters because transformation doesn’t happen at the strategy layer alone. It happens when direction becomes action—when teams understand not just what to do, but how to do it differently.
When that translation layer lacks confidence or clarity, progress slows. Initiatives stall. Use cases remain isolated. Teams wait for stronger signals on how to move forward.
The result is a familiar pattern: Organizations investing heavily in AI, but struggling to turn that investment into consistent, enterprise-wide impact.
When AI stays tactical, transformation never gets out of the gates
Even in organizations where adoption is strong, the ceiling on impact often comes down to how leaders themselves engage with AI.
If leaders treat AI as a productivity tool, their teams will follow. Work gets faster—but not fundamentally different.
If leaders use AI to rethink decisions, challenge assumptions, and redesign workflows, something more meaningful starts to happen. New ways of working take hold. Teams begin to operate differently. Transformation becomes tangible.
Right now, most organizations are still closer to the first scenario. That’s not due to a lack of ambition. In fact, expectations are rising quickly. Nearly half of leaders (47%) are already factoring AI usage into performance evaluations, signaling a shift in how work is measured and valued. At the same time, one-third (33%) have eliminated or delayed hiring for roles they believe AI can handle.
And yet, many of the leaders making these decisions are still developing their own understanding of how AI should be applied. It creates a tension that’s hard to ignore. AI is reshaping expectations faster than leaders are building the capability to guide that change.
Capability is emerging as the true differentiator
If there’s a clear signal in the data, it’s this: Training changes outcomes.
Leaders who’ve participated in structured, leadership-focused AI training consistently outperform those who haven’t. They’re more confident in their decision-making. More likely to redesign workflows. More likely to establish clear standards for how AI should be used. And more likely to see adoption take hold across their teams.
For example, 96% of leaders who have completed leadership-specific AI training report regular team usage, compared to lower rates overall. 88% say they understand how to use AI tools without compromising data, versus 68% across all respondents.
These aren’t marginal gains. They represent a fundamentally different level of readiness. More importantly, they point to a shift in how organizations need to think about AI adoption. The question shifts from, “Do we have access to the right tools?” to “Do our leaders have the capability to apply them in ways that drive real outcomes?”
From experimentation to enterprise-wide adoption
For many organizations, AI is still in an experimental phase—pilots, proofs of concept, isolated wins.
Moving beyond that stage requires something different. It requires leaders who can guide teams through ambiguity without losing momentum. Who can connect AI capabilities to business priorities. Who can build confidence across their organizations, not just curiosity.
In other words, it requires a new kind of leadership. One that treats capability as a competitive asset. One that understands transformation isn’t driven by tools alone, but by the people who know how to use them effectively.
This is where the conversation around learning and development becomes central. Not as a support function, but as a strategic lever. Organizations that invest in building AI fluency across leadership levels—especially among those closest to execution—are the ones most likely to move from experimentation to sustained adoption.
Why humans still matter (now more than ever)
For all the focus on technology, humans still hold the key. AI doesn’t replace leadership. It raises the bar for it. And as AI takes on more operational tasks, the role of leaders becomes more—not less—important.
Judgment. Context. Decision-making. The ability to navigate change and bring teams along. These aren’t technical skills. They’re human ones. And they become even more critical in an AI-first world.
The organizations that pull ahead won’t be the ones that simply adopt AI fastest or buy into the most tools. They’ll be the ones that leverage purpose-built AI training solutions to build the capability to use it thoughtfully, strategically, and consistently across every level.
And that work doesn’t happen by accident. It’s built—skill by skill, leader by leader, and team by team.
Leading the evolution
For 15 years, General Assembly has focused on building the skills that move individuals and organizations forward. With EZRA’s one-to-one coaching, that work extends beyond capability into behavior—helping leaders not just learn new skills, but apply them in real-world contexts.
Together, and as part of LHH, this approach connects learning, leadership, and workforce transformation in a way that reflects how organizations actually operate.
Because closing the AI competency gap isn’t about introducing one more tool or running one more workshop. It’s about building confidence and competence. Creating clarity. And giving leaders a practical path from ambition to execution.
Explore how to build that capability and lead the AI evolution: https://generalassemb.ly/employers/ai-for-leaders.