The AI paradox: How Australia’s most risk-averse institutions became AI trailblazers

Australia’s most cautious institutions are quietly becoming global AI leaders. Here’s how confidence - not capability - is driving change.

In brief:

• Australia’s traditionally cautious institutions are rapidly embracing AI, despite public scepticism.
• General-purpose AI tools are being adopted bottom-up, often without formal oversight.
• Building AI confidence through change management is more critical than technical capability.

Only 37% of Australians believe the advantages of artificial intelligence outweigh its risks. So, you wouldn’t expect to find some of the world’s most ambitious enterprise AI rollouts here. But that’s exactly what’s happening.

Across the nation, traditionally cautious and highly regulated institutions are rapidly advancing their adoption of artificial intelligence. Thousands of employees are being onboarded into AI-augmented workflows. General-purpose tools are embedded into daily tasks. The transformation is well underway.

And yet, public scepticism is high. Media coverage frequently highlights concerns such as job displacement, misinformation, and data privacy risks. Findings from the latest EY AI Sentiment Index Survey underscore this hesitancy: Australians rank among the least comfortable with AI globally, with nearly one in three outright rejecting it.

The contradiction is striking.

What’s going on?

The real constraint isn’t capability – it’s confidence

AI tools are improving almost weekly, becoming faster, more accurate, and more efficient.

The capability gap is widening – between those who know how to use AI tools – and those who don’t. That’s why change management is now business critical.

Driving AI adoption is like activating a flywheel – it takes real effort to get moving, with friction, fatigue and false starts. But with the right support, momentum builds. Confidence grows. And soon, what once felt immense effort is easy.

Stop overengineering – your people are already using AI

Here’s something I see daily: too many organisations are dedicating substantial resources to develop tailored solutions from the ground up. Building these highly specialised tools requires expert personnel, such as data scientists, long development cycles, and significant investment. By the time they launch, they’re often outdated.

Meanwhile, employees are experimenting with general-purpose AI tools to help create content, summarise reports, and automate admin tasks – often without formal training or permission. The tools they are using are intuitive, powerful and increasingly agentic – able to act on instructions independently, not just via chat. And these tools are being adopted from the bottom up, not the top down.

Don’t ask “What’s the use case?”

I’m often asked: “What’s the use case for AI?” This perspective misses the bigger picture.

We don’t ask for the use case of a laptop. We just use it for everything. AI is becoming the same. It’s the new layer between people and their work. A single pane of glass that helps us think, write, analyse, decide.

What matters now is not where AI fits, but whether your people are ready to use it.

Change is hard – but necessary

I’ve been working on the frontline of AI adoption programs and can attest that the initial phases are often challenging and resource-intensive. The learning curve is steep. But with the right support, hesitant teams become confident ones.

And the change is happening, whether we like it or not.

Leaders must stop waiting for perfection or permission – the worst AI we’ll ever have is what we’re using today. Every week it improves. That means every week you wait, the gap grows.

What leaders can do next

1. Recognise the significance of general-purpose AI tools: These aren’t side projects anymore. They’re becoming the backbone of productivity. Instead of focusing on developing custom applications through isolated projects, prioritise leveraging robust, ready-to-deploy foundational AI solutions to enhance efficiency and adaptability.
2. Drive AI literacy and change management: This isn’t a tech rollout. It’s a behaviour change program. Focus on upskilling, lead by example, and build communities of practice.
   
   

Organisations that invest in AI capability today are strategic and forward-looking. These efforts not only build capability but also foster confidence within teams. Once momentum is established, growth and innovation become exponential.

In a nation known for caution, it’s precisely that discipline – and a growing confidence – that’s turning Australia into an AI leader.