AI Isn’t Just for the Young. Senior Leaders, Don’t Count Yourselves Out.

The hype says AI belongs to the young. Digital natives who spend their evenings experimenting with prompts, who aren’t weighed down by decades of career baggage, who are quicker to try and fail.

Yet in senior leadership positions, I often see the opposite reaction. Many step back, delegating AI to younger colleagues because they feel they can’t adapt. I’ve heard it first-hand in conversations with family and with people in the twilight of their careers. They assume AI is “too late” for them, or that it’s only for the next generation. The reality is, it’s not.

That youthful energy is critical to any organisation, but it only goes so far on its own. For those further along in their careers, there are two more truths worth adding.

Curiosity and context are both must-haves. Youth fuels experimentation, while senior leaders embed change into the fabric of the business. It takes both for AI to move from hype to real transformation.

AI transformation isn’t just about tools or prompts. It’s about embedding technology into the bigger picture. As Frances Valintine CNZM (founder of academyEX) puts it:

“Senior leaders have the real advantage with AI because they already hold the context: customers, risk, regulation, and culture".

Here’s how that context shows up in practice:

And we see this playing out in organisations who apply their business context to guide AI:

Across each example, the tool is only half the story. What makes the difference is the context senior leaders bring.

That word context is doing a lot of heavy lifting. It is what separates novices from experts, and it is exactly where the AI debate has shifted.

Even on the technical side, leaders like Andrej Karpathy (OpenAI) and Tobias Lütke (Shopify) have been pushing the industry to move beyond prompt engineering toward context engineering, giving AI the right data, examples, and framing to improve results.

That is the technical view of context. But as we have seen, organisational context is just as, if not more, critical. It is the accumulated judgement of business models, customer realities, risk, regulation, and culture, context that only senior leaders can provide.

Think of it this way:

Neither works alone. The organisations that win will combine both: the fluency and experimentation of younger leaders (yes, Gen-Z deserve a seat at the leadership table) with the judgement and organisational context of senior leadership. That’s the bridge that turns AI experiments into enterprise value.

But that bridge only works if senior leaders step onto it.

Too many leaders count themselves out before they even start. They see AI as too technical or too late to learn. But their decades of experience are precisely the advantage AI needs.

And it raises an obvious question for those further along in their careers: how can you lead with AI if you don’t fully understand the tools?

The good news is that this revolution plays to their strengths.

Unlike past revolutions that demanded specialist knowledge, this one runs on tools that fit into everyday workflows. The leaders who embed AI into practice, culture, and resilience will define the next decade.

You don’t need to be a technical expert to lead with AI, you just need enough fluency to apply your judgement. It means building confidence with the tools and knowing how to use them strategically. Take prompting:

The difference isn’t the tool, it’s the framing. Leaders bring context about brand, audience, and tone that AI alone can’t supply. Leadership context applied to AI creates an advantage that compounds:

The tools are already here. Everyday platforms like ChatGPT, Perplexity, and NotebookLM are already in your hands. The advantage comes when leaders apply them with strategic intent.

What multiplies the results is expertise (in other words, context). Leaders’ experience and judgement multiply the results, which is why leaning in early matters. The edge now lies in how AI is applied strategically, not in discovering the tools.

The challenge isn’t recognising AI’s importance. It’s building the confidence to lead with it, and that only comes through applied learning.

Too much AI learning today is theoretical or done in isolation. It doesn’t stick. What makes the difference is anchoring learning in practice and context, connecting directly to a leader’s real work.

That’s why programmes like the Master of Technological Futures at academyEX flip the model. Every project ties back to the workplace, streamlining admin, testing scenarios, reshaping decisions, so leaders learn by doing, not just theory.

The approach is structured: classifying workflows as automation or augmentation, simulating incentives, and trialling tools like ChatGPT, Perplexity, and NotebookLM on live challenges. The goal isn’t chasing the newest platform, it’s learning how to apply AI strategically.

Confidence builds through safe, supported testing, no coding required, and making values-driven choices about which tools to scale and how to govern them responsibly. And because it’s done in cohorts, leaders share discoveries across industries, building a collective intelligence and future-proofed thinking: treating AI as an evolving toolkit, and leading teams with adaptability as technologies continue to change.

This article was co-created in partnership with academyEX, sponsor of The AI Corner newsletter and podcast.