74 per cent of AI's value is going to 20 per cent of companies. What does that mean for the other 80?

PwC published a study this week that put a number on something many people in business have been feeling. Of all the financial gains being generated by AI across the global economy, 74 per cent are being captured by just 20 per cent of companies. The top performers are generating 7.2 times more AI-driven revenue and efficiency gains than the average competitor. The study surveyed 1,217 senior executives across 25 sectors and multiple regions.

The headline is attention-grabbing, and the initial reaction for a regional business owner might reasonably be: here is another technology wave where the big end of town wins and the rest of us watch. That reaction is understandable. But the details of the PwC study tell a more nuanced story, and one that is arguably more relevant to regional Australian businesses than the headline suggests.

What the leaders are actually doing differently

The most important finding in the PwC study is not that some companies are making more money from AI. It is why they are making more money. The top-performing companies are not simply deploying more AI tools or spending more on technology. They are using AI as a catalyst for growth and business model change, particularly by pursuing revenue opportunities that cross traditional industry boundaries.

PwC calls this "industry convergence," and it is the single strongest factor the study found for predicting AI-driven financial performance. Stronger than efficiency gains. Stronger than the number of AI tools deployed. The companies getting the most value from AI are using it to do new things, not just to do old things faster.

This distinction matters for regional businesses. The dominant narrative around AI adoption has been about productivity: automate this process, speed up that report, reduce headcount in this department. And productivity gains are real. But PwC's data suggests that the companies treating AI purely as a cost-reduction tool are not the ones capturing the most value. The ones pulling ahead are those using AI to enter adjacent markets, develop new service offerings, or fundamentally rethink how they deliver value to customers.

The gap is not about technology access

It would be easy to read the PwC findings and conclude that the gap is about resources. The 20 per cent have more money, more data scientists, more compute. And there is some truth to that. But the study found that leaders are nearly twice as likely to use AI in what it calls "advanced" modes: executing multiple tasks within defined guardrails, or operating in autonomous, self-optimising configurations. These are not just descriptions of having better technology. They are descriptions of having clearer thinking about what the technology is for.

This is where the finding becomes relevant for a 15-person agribusiness in the Wimmera or a seafood processor in Lakes Entrance. The gap between the top 20 per cent and everyone else is not primarily a gap in computing power or engineering talent. It is a gap in clarity of purpose. The leaders know what problem they are solving with AI and how it connects to revenue. Everyone else is still experimenting, or worse, deploying AI tools because they feel they should.

What this looks like in regional Australia

Consider the Stanford AI Index, also released this month, which found that organisational AI adoption has reached 88 per cent globally. Four in five university students now use generative AI. The tools are no longer scarce or inaccessible. The barrier has shifted from "can we access this technology" to "do we know what to do with it."

For a regional Australian business, this reframing is important. You do not need to compete with the technology budgets of a multinational. You need to be clear about which specific problems in your operation or your market AI can help you solve, and then commit to actually using it for those problems rather than running generic pilots that go nowhere.

A grain trader who uses AI to analyse market signals and logistics data to find pricing windows that manual analysis would miss is doing something closer to what PwC's leaders are doing than a corporation that has deployed an enterprise AI platform but has not connected it to any revenue outcome. A citrus packhouse that uses computer vision to grade fruit more accurately and consistently, reducing rejection rates and opening access to premium export markets, is using AI for growth, not just efficiency.

The pattern we see at ARAIN is that regional businesses often have advantages that the PwC study does not capture. They are closer to their customers. They understand their operations intimately. They can make decisions and implement changes faster than large organisations with layers of approval. The constraint is rarely access to AI tools. It is knowing where to start and having the confidence to commit.

The honest assessment

The PwC study has limitations worth noting. It surveyed senior executives, not small business owners or operators. The 25 sectors it covers skew toward industries with large corporate players. When PwC talks about the "other 80 per cent," it is mostly talking about mid-sized and large companies that are underperforming relative to the leaders, not about a 10-person operation in regional Australia. The study's conclusions do not translate directly to the scale and context of most regional businesses.

What does translate is the core insight: using AI for something specific that connects to how you make money works better than deploying AI broadly and hoping for results. That principle holds whether you are running a $50 billion enterprise or a $5 million farm operation.

The Stanford AI Index adds another relevant data point. The estimated value of generative AI tools to US consumers reached $172 billion annually by early 2026, with the median value per user tripling between 2025 and 2026. People are getting better at using these tools over time. The value compounds with familiarity, which means starting now, even in small ways, builds capability that pays off later.

Where to go from here

If you run a regional business and the PwC headline made you feel like you are already behind, take a breath. The study is describing a pattern among large corporations, not a verdict on smaller operators. The principles that separate the leaders from the rest, clarity of purpose, focus on revenue not just cost, willingness to rethink how the business works, are things that regional businesses can apply at their own scale.

Start with a specific problem that costs you time, money, or missed opportunities. Use the AI tools that are available today to address it. Measure whether it helps. Then decide what comes next. That is closer to what the top 20 per cent are doing than any amount of unfocused experimentation, and it does not require a dedicated AI team or a six-figure technology budget to begin.