Can Australian businesses afford to waste $557 million?

Australia’s National AI Plan sets a bold ambition for artificial intelligence as a strategic lever for productivity, competitiveness and economic growth. It’s exciting for technologists and business leaders alike, but the reality is AI won’t work without a solid foundation — something most businesses do not have ready yet.

The foundation on which AI must be built needs to be modern, workflow-centric and data-ready — and the fact that it’s not there yet is not just inconvenient, but costly too. I often describe my role as a CTO as a ‘translator’ between cutting-edge technology and practical business outcomes. Right now, my biggest translation challenge isn’t understanding AI and its benefits — it’s convincing businesses to ensure the underlying systems are fit enough for purpose to empower AI to scale.

The modernisation paradox that’s costing us millions

Yes, organisations know exactly how much there is to gain from AI. But the truth is they aren’t yet able to capitalise on the opportunity due to the outdated systems that take up precious time, talent and budget. And even less talked about is how much they’re losing by being unable to modernise the very systems that AI relies on.

Recent research from Pegasystems and Savanta shows that Australian enterprises are burning over AU$550 million annually as a result of legacy systems. 88% of business leaders believe time, money and resources are being wasted maintaining these systems, but ironically, Pega’s research finds the effort to modernise these systems is the greatest contributor to the financial cost itself.

This brings us to the catch-22: businesses are gaining more technical debt whether they choose to continue using legacy technology or attempt to upgrade it to newer systems. In other words — they’re stuck in a modernisation paradox.

If Australia is serious about its AI ambitions, the real question is less about funding exciting new AI pilots, and more about businesses being able to adopt AI at scale across core operations where data flows freely, decisions can be automated in real time, and insights drive outcomes. But legacy systems simply can’t support that level of agility.

Modernising for AI: an ongoing strategic priority

Breaking the modernisation paradox needs a clear strategy to prevent or minimise the accumulation of even more technical debt. This means taking an enterprise-wide, ongoing approach, rather than treating technical debt as a ‘project’.

But before you can start to modernise legacy systems, leaders must ensure all stakeholders are on board — including developers — and aligned on the need to manage technical debt. If needed, reframe modernisation in a positive way: think of it as ‘continuous application health’, and highlight the value and benefits to the whole organisation. Fundamentally, it should be seen as an investment by all stakeholders, not a cost.

Once everyone is aligned, it should become a ‘business as usual’ activity — first stopping the bleeding, then investing in the sustainable improvement.

Start by preventing new technical debt. Establish clear guidance and expectations for stakeholders on best practices and develop processes that encourage code quality and reuse, especially in long-lived platforms. Only then can you turn to managing the existing technical debt. Balance developers who excel at building new features, with those who thrive on fixing, refactoring and improving existing systems. Both roles are equally important for innovation.

It’s important to remember to adopt a phased approach: systems should be updated incrementally, one step at a time, instead of everything all at once. It’s beneficial to use compliance updates to remedy and restructure applications, adopt new features and best practices while going live, followed by continued optimisation. This means avoiding accumulating hidden debt by ensuring that updates don’t leave the application operating suboptimally. Continuous learning and improvement will ensure performance, usability and future readiness.

Fixing the foundations to unlock the benefits of AI

While the urgency to modernise legacy systems is clear, the emergence of AI itself is now reshaping how this transformation can be achieved. Applied at design time, AI agents are increasingly able to automate and streamline the most complex aspects of legacy modernisation, reducing the time, cost and risk traditionally associated with these projects.

Rather than simply layering AI on top of outdated infrastructure, forward-thinking enterprises should prioritise AI initiatives that use design-time intelligence to accelerate their path off legacy systems. This approach not only helps break the modernisation paradox but also ensures that the foundations for AI are robust, scalable and future-ready.

Australia’s AI ambitions are inspiring, but without tackling technical debt, businesses risk becoming spectators rather than participants. Modernisation isn’t easy — but neither is the alternative of falling behind.

The organisations that will succeed will treat modernisation as a strategic investment, balancing new development with rectification and optimisation, and embedding continuous governance, reuse and best practices into their culture.

When these foundations are in place, AI can stop being an experiment and start driving real business outcomes resulting in faster decisions, better customer engagement, and improved competitiveness under the National AI Plan.

Image credit: iStock.com/simonkr