AI is changing the rules of competition.
Are businesses thinking big enough?

Three shifts in competitive advantage worth considering after Open Summit AI Adelaide.

By Melanie Osborne | Founder, Legato Communications

I attended Open Summit AI in Adelaide on 29 October, where there was plenty of discussion about the pace of AI development and what it means for business.

What interests me most isn’t necessarily what the technology can do, but how it could change some of the assumptions we’ve built our businesses around.

That being big brings an advantage. That brands compete primarily for human attention and preference. And that growth comes from doing more of what we already do, only better.

AI is beginning to challenge all three.

While the immediate productivity gains are significant, I suspect the longer-term implications could be far more interesting.

 

1. Could AI change the advantage of being big?

For decades, larger businesses have enjoyed advantages that smaller competitors simply couldn’t match. Bigger budgets, specialist teams, established infrastructure and the resources to invest in new capabilities.

AI is beginning to narrow some of those gaps.

Smaller businesses can now access capabilities that once required substantial teams or budgets. Research, analysis, content development, coding and increasingly sophisticated operational tasks can all be supported by AI.

But I wouldn’t write off the advantages of scale just yet.

Large organisations have something smaller businesses often lack: years of proprietary data, institutional knowledge, established customer relationships and accumulated expertise.

In an AI-enabled world, those assets could become even more valuable.

The catch is that having access to vast amounts of information doesn’t automatically translate into better decisions. Particularly when that knowledge is scattered across departments, buried in legacy systems or difficult to access.

Equally, giving a small business access to sophisticated AI tools doesn’t automatically make it a more capable competitor.

It’s what each organisation does with those resources that matters.

Smaller businesses may have the advantage of agility. Larger businesses have the depth of knowledge, data and resources to draw on.

Perhaps the real competitive advantage will increasingly depend less on the size of an organisation and more on how effectively it puts its resources to work.

 

2. What happens to brands when AI starts making the shortlist?

We’ve spent decades thinking about how brands influence people. Building awareness, establishing credibility, creating preference and giving customers a reason to choose one business over another.

But AI is beginning to change how those decisions are made.

Imagine a company looking for a new investment manager, law firm or technology partner. Rather than spending days researching the market, they ask an AI assistant to identify and compare the most suitable providers.

The resulting shortlist could shape the entire decision-making process, potentially before anyone has visited a company website or spoken to its team.

For those of us working in brand strategy, this raises some fascinating questions.

What determines which businesses are recommended? How accurately do AI systems understand a company’s expertise, reputation and positioning? And how much influence will brands retain over the way they’re presented?

I don’t believe this makes traditional brand strategy any less important.

If anything, the fundamentals of clear positioning, differentiation and credibility become more valuable.

But brands will need to think more carefully about how their expertise is communicated, evidenced and understood, both by people and by the systems increasingly influencing their decisions.

This is particularly relevant in financial services, professional services and technology, where purchasing decisions are complex and trust takes time to build.

And there’s an important distinction here. Being discoverable by AI isn’t necessarily the same as being preferred.

Getting onto the shortlist is one thing. Giving someone a compelling reason to choose you is quite another.

 

3. Are we thinking big enough about what AI makes possible?

Much of the conversation around AI still centres on productivity.

How can we do things faster? Automate more tasks? Reduce costs?

Fair enough. There are significant efficiencies to be gained, and for many organisations these are the obvious starting point.

But I wonder whether we’re spending too much time thinking about how to improve existing processes, and not enough questioning whether those processes still make sense.

If you were starting a business today, knowing what AI now makes possible, would you build it the same way?

Would you structure your teams around the same functions? Deliver services through the same processes? Maintain the same cost base or charge customers using the same model?

I suspect many businesses would make some very different decisions.

There’s a big difference between making an existing business model more efficient and questioning whether it’s still the best way to create value.

For established organisations, that might mean rethinking how services are delivered, where expertise sits or how customer relationships are managed.

For smaller businesses, it could mean entering markets or offering capabilities that previously seemed well beyond their reach.

Not every process needs reinventing, of course. But there’s a risk in becoming significantly better at doing things that may no longer be the right things to do.

 

Cropify: AI applied to a problem worth solving

One of the more interesting examples connected to the Adelaide summit was Cropify, a local agritech business whose co-founder, Andrew Hannon, was among those presenting at the Fishburners Pitch Night.

Cropify is tackling a longstanding problem in agriculture: the grading of grain to determine its quality and commercial value.

Traditionally, this has involved trained graders visually inspecting samples, a process that takes time and can produce varying assessments.

Cropify uses AI and computer vision to analyse grain samples in minutes, helping deliver more consistent and objective results.

What interests me isn’t simply the speed of the technology. It’s the problem they’ve chosen to solve.

Grain grading is a critical part of the agricultural supply chain. It influences pricing, commercial decisions and trust between buyers and sellers.

Improving that process has clear commercial value.

And that’s what makes this such a compelling application of AI. It’s not technology looking for a purpose. It’s a business identifying a genuine industry problem and finding a better way to address it.

I suspect there are plenty of opportunities like this across other industries, where established processes have simply become accepted ways of working.

 

Looking beyond the technology

Having spent much of my career working with large organisations, and the past ten years running Legato, I’ve seen the advantages and frustrations of operating at very different scales.

Large businesses can draw on extraordinary resources and expertise. But established structures, competing priorities and layers of decision-making can also make change surprisingly difficult.

Smaller businesses have their own constraints, particularly around capacity and investment. But they can often move faster, experiment more freely and challenge established ways of working.

AI adds another dimension to that equation.

I don’t think the businesses that benefit most will necessarily be those with the biggest AI budgets or the longest list of tools.

What matters is understanding where your business creates value, what makes it different and which assumptions are worth challenging.

For business leaders, that means looking beyond the immediate efficiencies and asking some more fundamental questions.

Where will our competitive advantage come from? How will customers find and choose us? And what would we do differently if we were designing our business for the opportunities ahead, rather than preserving the way we’ve always operated?

We’ve spent a lot of time talking about what AI can do. Perhaps the more important question is what we should be doing differently because of it.