Inequality, displacement, and the risk of AI colonialism.

Who gets lifted by AI and who gets left behind?

Every major technological shift in history has changed the distribution of opportunity. But AI is different in one crucial way: it doesn't just change what we do, it changes who gets to participate in the world that's being built.

For many, AI will open doors to new careers, new businesses, and new forms of creativity. For others, it will quietly remove the pathways they've relied on for security. And if we're honest, these impacts won't land evenly. They never do.

We're at real risk of building an AI-driven world where people who benefit most are those who were already well positioned to succeed, while those living without access to capital, infrastructure, or digital literacy slip further behind.

This is where the concept of AI colonialism becomes uncomfortably relevant.

Where technology deepens existing divides

There's a widening gap forming between communities with access to high-quality data, compute, and capability, and those without it. Nations with strong digital economies can build and deploy AI models that amplify their growth. Meanwhile, smaller countries, Indigenous communities, and regions without robust infrastructure often end up becoming consumers rather than creators in the intelligence economy.

History has shown us what happens when power is distributed unevenly. The groups with access extract value; the groups without it become dependent on someone else's systems, someone else's rules, someone else's worldview.

If we don't intervene intentionally, AI will follow the same pattern. The global south risks becoming a testing ground for AI systems built elsewhere, using values that may not align with the communities they are meant to serve. And closer to home, Māori and Pasifika peoples, already navigating structural inequities, could face another wave of exclusion unless we deliberately bring them into the design and decision-making process.

The human impact behind "workforce transformation"

We often talk about automation in tidy language: increased efficiency, cost reduction, productivity gains. But behind that language are real people, real families, and real identifies.

For many workers, their job is more than a pay check. It's a sense of purpose. It's belonging. It's a way of contributing to their whānau and community. When AI removes that role without offering a meaningful pathway forward, the impact is not just economic; it is deeply emotional.

Some people will transition into new roles. Some will retrain. Some will thrive. But many won't have the support systems, time, or resources needed to make that leap. They're not resistant. They're abandoned.

To talk about AI ethically, we must talk about people. Especially those who don't get a seat at the table when disruption plans are being drafted.

The responsibility of leaders: fairness is not optional

Ethical leadership in the age of AI means asking uncomfortable questions early:

• Who benefits?

• Who doesn't?

• Whose voices are reflected in the systems we're building?

• Whose values?

• Whose language?

• Whose lives become harder as a result?

The easy path is to optimise for efficiency. The ethical path is to optimise for equity.

If we want AI to support human flourishing, we must build it with, for, and alongside the communities who stand to be most affected. And we must ensure the future we're creating is one where everyone has access to opportunity, dignity, and choice.

We need to ensure progress reaches everyone.