Australian Businesses Are Adopting AI. The Hard Part Is Turning It Into Value.

Australian organisations have moved quickly on AI.

According to the Australian Bureau of Statistics, 12% of Australian businesses reported using artificial intelligence in 2024–25, up from just 1% three years earlier. In some sectors, adoption is considerably higher. Information, Media and Telecommunications leads the way, followed by industries such as Financial and Insurance Services and Professional, Scientific and Technical Services.

The technology is getting into organisations. That was never going to be the difficult part. The difficult part is deciding where AI genuinely belongs, changing the way work gets done around it, and proving that the investment has improved something that matters.

Because an organisation can have hundreds of people using generative AI and still be no more productive. It can launch impressive pilots that never scale. It can automate a process nobody should have been running in the first place. And it can spend a significant amount of money without being able to answer a straightforward question from the executive team: what have we actually got for it?

The AI conversation is moving beyond experimentation

Most executive teams are no longer debating whether AI will affect their organisation. They know it will. The conversations we're seeing are different now.

Where should we invest? Which problems are worth solving? What should we scale? What should we stop? How do we manage the risks without creating a governance structure so heavy that nothing moves? And, increasingly: where is the value?

That last question matters. The ABS reports that while Australian businesses are increasingly adopting digital technologies, only 7% measure the contribution digital activities make to overall business performance.

That gap should concern any executive responsible for a significant technology or transformation portfolio. If you can't see the contribution, you can't confidently manage the investment.

Technology doesn't create value on its own

We've seen this movie before. Cloud. ERP. CRM. Digital transformation. The technology changes. The pattern doesn't.

An organisation buys a platform with a compelling business case. The implementation receives executive attention. The project goes live. Then comes the harder work.

Processes need to change. Decisions move. Roles evolve. Teams need to work differently. Leaders have to reinforce new behaviours. Old workarounds have to disappear. That's where value is either created or quietly lost.

AI is no different. The technology might be more powerful and the pace of change considerably faster, but the fundamentals remain stubbornly familiar. Technology creates an opportunity. The organisation has to create the outcome.

Start with the value, not the use case

There is a lot of pressure to demonstrate progress on AI. That pressure can lead organisations to start with the technology: what could we do with this? A better executive question is: where do we need to improve performance?

• Where is the business carrying unnecessary cost?
• Where are skilled people spending time on work that shouldn't require their attention?
• Where are decisions slow because information is fragmented?
• Where is customer experience being compromised?
• Where is growth being constrained?

Those questions lead to better investment decisions because they start with the business. AI may be part of the answer. It may not. Either way, the organisation is focused on solving the right problem.

The real work sits around the technology

The most successful technology transformations are rarely technology projects. They force decisions about the organisation itself. AI will be no exception.

For many businesses, the implications will reach into operating models, workforce design, capability, governance and the way decisions are made. The introduction of the technology is simply the visible part. The harder questions sit underneath it.

• Who owns the outcome?
• What work should change?
• What capability do we need to build internally?
• What decisions should remain human?
• How do we redesign processes rather than simply accelerating the existing ones?

Those aren't questions an AI platform can answer. They are leadership questions.

Don't confuse activity with progress

The number of AI licences purchased is not a performance measure. Neither is the number of pilots launched. Usage is useful to understand. It is not the outcome.

Executive teams need to be able to see what has changed as a result of the investment. That might mean:

• Reduced operating costs
• Faster cycle times
• Greater capacity
• Better decisions
• Improved customer experience
• Reduced risk
• Revenue growth

The measure will depend on the reason for making the investment in the first place. The important thing is that it exists. Without a clear connection between investment and outcome, organisations can create a lot of activity around AI without ever building a compelling case for the value it is producing.

The next phase is an executive challenge

Australian businesses have embraced AI faster than many expected. The next challenge is more demanding. It requires leaders to make choices about where to focus, what to redesign and what success actually looks like. It requires enough discipline to avoid chasing every new capability and enough ambition to avoid being left behind.

The organisations that get the most from AI won't necessarily be the ones using the most technology. They'll be the ones that make the best decisions about where it belongs. That's the transformation challenge.

At MethodWerx, we work with organisations to connect technology investment to the broader changes required to create business value — from strategy and operating models through to delivery, adoption and benefits.

AI can change the technology landscape quickly. Turning that change into business value takes more than technology. It takes deliberate transformation.