96% of Aussie Businesses Are Using AI. Most Have No Idea If It’s Working.

Almost every Australian business is using AI. Most cannot tell you whether it’s working.

That’s the core finding from ReadyTech’s new survey of 311 Australian organisations. Ninety-six per cent are using or exploring AI. Seventy-one per cent expect their AI investment to grow over the next 12 months. And yet 43% of those same organisations are still in the earliest stages of AI maturity. Adoption is near-universal. Measurement is not.

Spending has outrun accountability

There’s a difference between having AI in your stack and knowing what it’s doing for you. ReadyTech CEO Marc Washbourne put it plainly: “Too many organisations still lack clear productivity baselines and don’t consistently measure the value AI delivers, making it difficult to demonstrate ROI or know where to invest next.”

That failure mode is familiar. You adopt a tool. It gets used. You assume it’s helping. Then you need to justify the next spend and realise you never set a baseline to measure against. This is the pattern playing out across Australian businesses right now, investment going up, measurement staying flat.

Productivity is the main stated reason for AI investment. Cost reduction ranked eighth. That’s the right instinct. But productivity is one of the hardest things to measure unless you define it before you start.

The governance hole

One in six organisations, 16%, have zero AI governance in place. No policies about how AI is used, what data it touches, who reviews the outputs.

The top risks respondents flagged: hallucinations and misinformation (50%), privacy breaches (49%), inaccurate outputs (47%). These aren’t abstract. IBM puts the average cost of an Australian data breach at AUD $4.26 million, not far from the $5M–$20M+ annual AI budgets some of these organisations are now running. Governance isn’t paperwork. It’s how you avoid finding out your AI tool has been leaking customer data for months.

The data problem underneath

Seventy-nine per cent of organisations said they’d benefit from a unified data layer. Only 58% say their systems actually provide one. Without connected data, you can’t measure what AI is doing. You have outputs scattered across systems but no clean view of whether any of it improved. This is what “43% still in earliest stages” actually looks like in practice, not ignorance of AI, but a foundation that isn’t solid enough to build on.

This applies at small business scale too

The survey covered large organisations spending tens of millions annually. Easy to read as someone else’s problem. But the dynamics are identical at smaller scale. A small business using three or four AI tools faces the same measurement failure. You’re paying subscriptions. You’re spending time integrating things. Are you actually saving time? Do you know?

Measuring AI ROI doesn’t need a data team. It needs a decision, made in advance, about what you’re trying to improve. That’s the practice 43% of surveyed organisations haven’t built yet. If you have it, you’re already ahead of most.

Three things worth doing now

1. Set a baseline before your next AI tool. Pick one metric the tool is supposed to move, time spent, error rate, output volume. Write it down before you start. Without this, you’ll never know if the tool is working.
2. Run a quarterly AI cost vs output check. Add up what you’re spending each quarter, then ask honestly: what has changed? If you can’t point to anything, the tool either needs measuring or needs cutting.
3. Document what AI touches customer data. If any tool handles customer information, note it down, what data, which tool, where it goes. This takes less than an hour and is the minimum for responsible use.

Near-universal adoption with patchy measurement and a 1-in-6 governance gap is the current state of AI in Australian organisations. You don’t need a strategy document to do better than that. A baseline, a quarterly check-in, and a short list of what your AI tools touch will do it.

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