Two years ago ChatGPT burst onto the scene as AI's coming-of-age moment for the mainstream, non-technical business leader.
2 years in, and most companies are only just piecing together fragments of an AI plan.
Section School is one of my absolute favourite resources for AI research. According to their recent "AI Proficiency Report" (download here) released in January this year, only 9% of surveyed knowledge workers qualify as "AI Experts" (1%), or "AI Practitioners" (8%).
That means that the majority of the workforce — spanning "AI Experimenters" (34%) and AI Novices (47%) — are still playing around the edges and experimenting with basic AI skills, knowledge and use cases, while the "AI Skeptics" (11%) remain hesitant, unsure how to proceed or if they should at all.
To me, these numbers show the struggle going on out there for most businesses to assemble something transformational out of AI. They're stuck (still) between excitement and uncertainty.
The reasons given within Section's AI Proficiency Report for this uneven adoption are multifaceted, but two of the most important are;
- Company policies influence behaviour — many senior leaders I talk to are still shocked to find that 43% of employees in companies that outright ban AI still use it weekly by bringing their own personal AI subscriptions to their desks.
- The AI literacy levels and skill bases of senior leadership and middle management. Or more accurately, the lack thereof.
And it's point #2 above that I'm going to focus on in this essay.
The Section School report makes what I think is a pretty telling observation... in organisations where AI is openly embraced, the presence of 'AI Experts' and 'AI Practitioners' is halved when direct managers discourage its use.
This tells me that leadership is the bridge that connects AI aspirations to organisational reality, shaping the trajectory of its integration at every level.
In other words; true AI adoption doesn’t begin with technology or tools.
It begins with leadership. AI literate and skilful leadership.
If companies truly want to become "AI-emergent" — established companies who have infused AI literacy, skills and innovations into every level of human process and product/service offering — they need to focus on educating and empowering their executive leaders and middle managers as a first priority.
Even before they start to educate and up-skill the rest of the workforce.
The 1980s Toyota parallel
Of course, I'm not breaking new ground here. The significance of leadership in driving transformation isn’t a novel concept.
Toyota in the 1980s revolutionised manufacturing with its 'lean production system' - a methodology that focuses on minimising waste while maximising productivity.
Toyota’s leadership took a really hands-on approach, embedding lean principles into every level of the organisation.
Middle managers were asked to act as both mentors and problem-solvers, facilitating small but transformative changes on the factory floor for the teams and employees they led.
Their emphasis wasn’t just on enforcing procedures but on building a culture of shared accountability and learning. This leadership-driven transformation turned Toyota into a global standard-bearer for operational excellence.
But management couldn't have played those mentor/guidance/advocacy roles unless they had been first-cab-off-the-rank to receive prioritised training and education, before the teams they led received that same training.
Ove the past couple of years I've witnessed AI adoption following a similar pattern (in the companies who are most successfully adapting to AI).
It’s not enough to just train technical teams or provide employees with access to AI tools. For AI to become a core competency, leaders need to be able to champion its use, understand its capabilities, and model (through behaviour) its integration into workflows.
Just as Toyota’s managers were the driving force behind lean manufacturing, today’s business leaders have to become the flag-bearing practitioners of AI. Through action and demonstration, by showing advanced understanding of AI and ability to apply it consistently to their own tasks, middle managers and senior leaders can become powerful enablers of AI change.
"Hey, is anyone else's face getting squashed back here at the top of this escalator?"
Why middle management holds the key
When it comes to AI, middle managers occupy a pretty unique and important position in organisations.
They’re close enough to frontline teams to understand day-to-day challenges but senior enough to influence organisational priorities.
So, if these managers lack AI literacy, it creates a bottleneck.
Employees might experiment with AI tools, but without guidance, their efforts often remain scattered and superficial.
Even worse, a manager who shows skepticism or discomfort with AI can discourage their teams from exploring its potential.
This isn’t just speculation; Section School’s report calls it out directly...
Even in companies that explicitly encourage AI use, if an employee’s manager discourages AI use in their work, they’re more likely to have lower AI proficiency.
On the flip side, when middle managers embrace AI, they act as catalysts.
When they're AI literate, it promotes a smooth and consistent flow-on of AI education, skills and (crucially) a culture that it's safe to experiment with AI.
In essence, they translate organisational AI goals into on-the-ground action.
Bridging the gap
So, what does it take to equip senior leaders for this role as the promoters and facilitators of AI literacy and skills throughout all strata of their organisation?
First, organisations need to prioritise AI literacy as part of leadership development.
This goes beyond just having a basic understanding what AI is; it requires a real hands-on approach.
Leaders need to experience first-hand what it feels like to breeze through a task with AI... 10/20/50/200% faster and more effectively than that same task used to take them manually.
They need to have many of those tactile experiences of the capabilities (and the limitations) of AI tools firsthand, in order to be able guide their teams effectively.
Second, I feel strongly that AI training has to focus on practical applications. Leaders don’t need to become data scientists, but they do need to understand how to use AI to solve business problems, improve efficiency, and drive innovation.
This might include workshops on crafting effective prompts, creating CustomGPTs for the 5-10 most important and regular processes that employees do regularly within the company, or highlighting case studies of successful AI use in their industry.
Lastly, I'd note that I see organisations who create a culture where AI experimentation is encouraged experience outsized results in terms of the pace and effectiveness of AI deployment through the ranks. By giving middle managers (and by association, the employees they manage) the freedom to explore AI without fear of failure, companies unlock their creativity and ingenuity faster and more transparently.
The ripple effect of AI-literate leadership
It's really clear to me in my work with SMEs right through to small enterprises, that when senior leaders and middle managers are given the AI literacy, skills and cultural safety to champion AI, the benefits extend far beyond just their immediate teams.
They set the tone for the entire organisation, signalling through their "walk" as well as their "talk" that AI isn’t just a passing trend and that it's becoming prioritised as a core competency within the company.
This initiates a cascading influence throughout the organisation...
Employees become more confident in using AI tools, cross-functional collaboration improves as teams find new ways to leverage AI, and the organisation as a whole becomes more agile and innovative.
This ripple effect can’t be achieved through policies alone. (While clear AI policies are essential for setting boundaries and ensuring ethical use, they’re not enough to drive deep adoption.)
Far more important than policies, is the human element — starting with skilled and AI literate leaders who inspire, guide, and empower their teams to explore what’s possible with AI.
A call to action for organisations
For companies looking to become AI-emergent, my encouragement to you is to start with your senior leadership teams and middle management.
Provide them with the training, resources, and support they need to become AI-literate and, eventually, AI-proficient. Empower them to lead by example, to mentor their teams, and to act as advocates for AI adoption.
The stakes are high.
The Section School AI Proficiency Report I've referred to throughout this essay tells a story of an anxious and overwhelmed workforce still trying to navigate the complexities of AI.
Without AI literate leadership, I think this anxiety will only deepen, and organisations will risk falling behind their more forward-thinking competitors.
There's another path though. The same one Toyota chose in the 1980s. When they prioritised training their managers first and foremost in what they believed would be a system of competitive advantage, they created a culture of continuous improvement that reshaped their industry.
In the same way, I firmly believe that organisations that prioritise developing AI-literate senior leadership and middle managers will be the winners in their industries over the next decade.
Got something to add? Chime in below...