Ten year+ ago, a group of management trainees — including me — sat around and discussed how the new corporate strategy impacts us and our team. We came from finance, economics, innovation, journalism, and the military. Only one of us had anything close to a technical background. Back then, we were knee-deep in financial modelling, M&A processes, CEO Office planning support, security briefings, in tight collaboration with our top executives that we were shadowing.

The company we worked for had just launched a clear and ambitious digital transformation strategy. It sounded bold, modern, and visionary. But for many of us, the technology behind it felt distant — something that happened in another part of the organization. While we focused on the metrics and the business cases, software teams were battling their own challenges: limited understanding from leadership, little appreciation for technical constraints, and a general disconnect between what was needed and what was understood.

I eventually crossed over into software development and product. And suddenly, I saw it from the inside: the gap. The frustration. The repeated struggles in explaining why development takes time, why technical debt matters, or why possibilities in technology were far greater than what the business could see.

Digital transformation, as many organisations learned, wasn't really transformation. In many cases, it was digitisation — turning paper into digital forms, optimising sales pipelines, or moving manual processes into data systems. Important, yes. But not transformative.

Meanwhile, some leaders were already thinking ahead — about data, structure, and scalable architectures. I worked in the Data Lake side of the organisation, where the conversations were about capturing information at scale, preparing for a future where data would drive everything.

Fast forward ten years. The same trainee group met again this week. Only now we're founders, top leaders, fund managers, and entrepreneurs.

And this time, the conversation is entirely different.

We talk about AI model differences — Anthropic vs OpenAI. We compare tools. We discuss use cases. We debate implementation. We test. We share across industries. The former financial analyst is now scaling a business with a team of one, powered by Claude. The technical trainee has fully re-skilled into full-stack development, the one with military background scaling personal and enterprise processes with multiple agents.

Who would have imagined this would be our table talk a decade later?

It tells us something crucial: this technological wave hits different.

Digital transformation was often for the few. AI transformation requires everyone!

AI literacy and adoption are no longer optional or limited to certain roles. It is not a tooling problem. It is not a knowledge problem. The barriers are dropping. The curiosity is rising. And unlike before, people want to understand — not because they were told to, but because they can immediately see the value.

Are we there yet? No. Not even close.

But this time, we're all invited. And we all need to show up.

What This Means

AI isn't a project. It's a capability. A mindset. A shared organisational language.

Here's what we can do — individually and collectively — to stay ahead:

As individuals:

As teams:

As an organisation:

AI is not the responsibility of a few experts. It's the opportunity of the many.

If digital transformation taught us anything, it's this: transformation fails when it becomes someone else's job. AI transformation will only succeed when it becomes everyone's job.

So, let's make sure everyone comes along for this wave.