Is AI Killing SaaS? What Australian Businesses Need to Build Next

Australia's venture capital market recorded A$5.1 billion in funding in 2025. On the surface, that is a number worth celebrating. It signals confidence, momentum, and a maturing startup ecosystem.

But headline numbers can obscure what is actually happening underneath them.

The composition of that capital ,where it is going, what it is backing, and what assumptions it is making, tells a more complicated and more important story. A significant share of that investment has flowed toward AI-enabled companies, particularly those positioned as infrastructure plays, applied AI platforms, or tools designed to replace existing software workflows.

And that trend is forcing a question that every founder, investor, and business leader in Australia needs to sit with seriously: is AI killing SaaS?

What Is Actually Happening to SaaS

To be precise about it — AI is not killing SaaS outright. But it is doing something that may ultimately be just as disruptive. It is commoditising large parts of it.

For the better part of two decades, SaaS scaled on a reliable model. Layer features. Build subscription revenue. Grow net revenue retention. The interface was the product, and the product was the moat.

That model is under genuine pressure now.

AI systems are increasingly automating entire business functions, not just assisting with them. When intelligence becomes embedded directly into workflows, the value shifts. It moves away from the interface and toward the underlying data, the models, and the depth of integration. A well-designed AI system does not need a polished dashboard if it is already embedded in how a business operates.

The consequence for SaaS is significant. Generic tools with shallow differentiation are exposed. Products built on thin feature sets, without proprietary data or deep ecosystem integration, are vulnerable to rapid displacement, not in years, but in months.

The Capital Allocation Problem

This is where the story gets more structurally concerning.

If a meaningful share of Australia's A$5.1 billion in venture funding is chasing incremental AI wrappers around existing software, essentially SaaS products with a language model bolted on, the ecosystem risks over-indexing on short-cycle applications that will not hold their value.

AI infrastructure and applied platforms will attract capital regardless. That is not the issue.

The issue is whether enough capital is finding its way to deep tech, the category of innovation that actually builds long-term national and commercial capability.

Advanced manufacturing. Biotech. Energy systems. Quantum computing. Climate technology. Foundational AI infrastructure. These sectors require longer time horizons and patient capital. They are harder to build. They are harder to replicate. And precisely because of that, they create something genuinely valuable: defensible intellectual property, real technical barriers to entry, and the kind of compounding capability that sustains competitive advantage across market cycles.

When capital over-rotates toward fast-cycle AI applications, it systematically under-funds the deep tech layer that everything else eventually depends on. That is a structural problem, not just an investment preference.

What Durable Advantage Actually Looks Like Now

For businesses navigating this environment, the strategic implication is clear. The moat can no longer be a user interface. It can no longer be a subscription model or a feature set. In an AI-accelerated world, those advantages compress faster than they can be built.

Durable competitive advantage now comes from five sources:

• Proprietary data assets. Data that a business has accumulated through its operations, relationships, or unique market position, data that cannot simply be replicated by a competitor with a larger budget. AI makes data more valuable, not less. Businesses that own distinctive data are building a structural advantage that compounds over time.

• Embedded ecosystem relationships. The deeper a product or service is integrated into how a customer operates, the harder it is to displace. Shallow integrations are vulnerable. Deep operational dependencies, where switching creates genuine disruption are a real moat.

• Regulatory positioning. In sectors where regulatory complexity is high like financial services, healthcare, energy, infrastructure, compliance capability and regulatory relationships create barriers that pure technology cannot easily overcome. Businesses that invest in this positioning are building something their competitors cannot simply copy.

• Capital intensity and technical complexity. Businesses that require significant capital investment or genuine technical depth to build are inherently more defensible. The lower the barrier to entry, the faster the commoditisation. Deliberately building in complexity through advanced engineering, specialised manufacturing, or proprietary processes creates a buffer against displacement.

• Network effects that compound over time. When a product becomes more valuable as more people use it, and when that value accumulates rather than plateaus, the business becomes progressively harder to challenge. These effects are rare, but they are the most powerful form of defensibility available.

  
  

Defensibility Is Structural

There is a mindset shift embedded in all of this that goes beyond product strategy.

In the previous era of SaaS, defensibility was often cosmetic. A better user experience. A cleaner interface. A faster onboarding flow. These things created switching friction, but they were ultimately replicable with enough engineering budget and time.

In an AI-accelerated environment, cosmetic defensibility disappears quickly. What remains is structural defensibility, advantages that are built into the architecture of the business itself, not the surface layer of the product.

This requires founders and leadership teams to think differently about what they are building and why. Speed to market still matters. But speed without depth creates businesses that are easy to copy and hard to defend.

The companies that will hold their value through this period and through the capital cycles and technological shocks that follow are the ones that are designing for depth from the beginning.

The Question Every Founder and Investor Should Be Asking

The strategic question here is not whether AI will continue to attract capital in Australia and globally. It will. That trend has enough momentum behind it to be essentially certain.

The question is whether that capital is building temporary advantage or long-term capability.

An AI wrapper around an existing SaaS product might generate strong early revenue. It might attract a funding round. It might look compelling in a pitch deck. But if the underlying business has no proprietary data, no embedded ecosystem relationships, no technical complexity that is hard to replicate the advantage is temporary, and the clock is already running.

The businesses and investors that will define Australian technology in the next decade are the ones asking harder questions now. Not just what can we build quickly, but what are we building that will be genuinely difficult to destroy.

That is a different kind of ambition. And in the current environment, it is the right one.