Can AI Truly Think Like Us : Bridging the Trust Gap Between Business Leaders and Artificial Intelligence

By Philip Coster

October 29, 2024

Trust, distilled into code. Sit with that thought for a moment.

In a world where companies pour billions into digital transformation, only to watch those efforts unravel, it’s tempting to wonder if trust could be built as surely as a line of code.

Nearly three-quarters of these initiatives collapse, a $2.3 trillion waste every year.

And it’s not for lack of technology or funds.

There’s a missing element, something beyond metrics and KPIs, something almost intangible: trust.

After three decades working in digital transformation, I can tell you, technology is only as powerful as the trust it earns.

The idea of an algorithm that amplifies human intuition rather than replacing it—that’s where the true potential lies.

If done right, AI wouldn’t just operate alongside us but deepen the connection between human judgment and machine precision, helping people make better, faster decisions.

But trust in AI?

That’s not a simple checkbox.

Well, ask Professor Tony Clear at Auckland University of Technology. He draws a disquieting analogy between our modern race for data and the brutal history of colonial land grabs. Professor Clear calls it the “terra nullius” mindset—the concept of claiming land deemed “empty” simply because it didn’t belong to the colonisers.

In this digital age, data has become the new territory, and the aggressive drive to control it bears eerie echoes of that past disregard.

Professor Clear’s analysis doesn’t just question the machines; it raises a critical point about the people behind them.

Can we trust those shaping the future of AI when history warns that unchecked control too often leads to exploitation?

Shoshana Zuboff echoes this truth in The Age of Surveillance Capitalism, arguing that today’s tech giants operate with a near-feudal grip over data, much like old-world empires.

She reminds us that the core issue isn’t whether we can trust AI, but whether we can trust the intentions behind it. For those of us who’ve watched this industry evolve, it’s a sobering thought. It’s not enough to wonder if the machine can be trusted; we need to question the people and power structures driving its development.

So, why do experienced executives hesitate with AI?

The answer isn’t as simple as a fear of the unknown.

We’ve seen technology come and go; adaptation is second nature.

But human bias is visible. It’s transparent, and in some ways, predictable. AI, on the other hand, is an enigma—a force that operates within a black box, making decisions that can seem both powerful and alien.

That gap—where trust should be—often becomes a chasm.

But the path forward is there.

Companies that prioritise transparency, that push ethical frameworks and rigorously uphold accountability, are setting a standard.

Consider AI as a collaborator, a co-pilot that enhances human skills, rather than one that seeks to replace them.

Organisations willing to install bias detection, whistleblower protections, and establish transparent AI roadmaps aren’t merely adopting a technology—they’re establishing trust in a space where ambiguity has often reigned.

By treating AI with the same ethical and operational respect as a human partner, they’re building something greater than mere efficiency. They’re crafting a future in which AI becomes a genuine ally.

Trust, though, is fragile.

It’s earned in careful, deliberate steps, often tested, sometimes strained, and if lost, it’s hard to regain.

The success of AI doesn’t hinge on machine precision or an edge in efficiency. It depends on a foundation of transparency, responsibility, and a vision that sees human complexity not as a weakness but as a strength.

Over my years, I’ve watched the digital revolutions that endure.

They’re built on more than quick wins or dazzling tech.

The revolutions that stand the test of time respect the human element and understand that technology should support, not override.

AI’s future isn’t about planting new flags or staking claims in digital frontiers.

It’s about merging the machine’s reliability with the subtlety of human experience, each one bolstering the other in ways that transcend mere calculation.

This path forward isn’t about bending humans to fit the machine’s mold.

It’s about designing machines that fit within the contours of human experience, that reflect our values, our ethics, and yes—our trust.

And that, I believe, is the only future worth building.