How to Build an AI-Resilient SaaS Company: The Defensibility Test for Founders

AI is rapidly reshaping the SaaS industry.

Some software companies will become dramatically more powerful as they integrate AI into their products. Others may find that AI agents quickly replicate features that once justified standalone software tools.

For SaaS founders, the strategic question is becoming increasingly important:

At YFM, we’ve been exploring this question with founders across our portfolio and through conversations with operators, AI specialists and our broader Entrepreneur Lab community.

While the technology is evolving quickly, a few patterns are already emerging.

What makes a SaaS company resilient to AI disruption?

Several characteristics tend to make software businesses more defensible in an AI-driven world:

1. Proprietary data – unique datasets competitors cannot easily replicate
2. Workflow ownership – software embedded in core operational processes
3. Regulated or complex industries – barriers to entry protect the product
4. Deep vertical expertise – specialised knowledge within a sector
5. Ecosystem integration – multiple systems depend on the platform
6. AI leverage – ability to utilise AI within the product rather than commoditising it

Let’s explore each of these in more detail.

One of the strongest sources of defensibility in software has always been proprietary data.

If your platform captures unique operational data, transactions, machine data, regulatory workflows, patient records or sector-specific insights, then over time you are building something far more valuable than a product feature.

You are building a data asset.

AI models improve significantly as they gain access to larger and higher-quality datasets, a trend highlighted in the Stanford AI Index Report.

A useful test for founders is simple:

If your company disappeared tomorrow, would that dataset disappear with it?

If the answer is yes, you may already be building a meaningful competitive advantage.

AI can replicate features surprisingly quickly.

But it cannot easily replicate years of real-world operational data.

The most durable software products tend to sit at the centre of how organisations actually operate.

Think systems that store decisions, approvals, compliance records or financial data, platforms that effectively become the system of record for a business process.

Even as AI automates more tasks, companies still need trusted systems where information is stored, verified and managed.

When a product sits at that centre point, AI tends to become a feature that strengthens the platform, rather than something that replaces it.

Regulated sectors like healthcare, financial services, insurance and government rarely change overnight.

Compliance frameworks, certifications, integrations and data requirements create real barriers to entry.

While AI may accelerate innovation, it does not remove those barriers. In many cases, it actually increases the value of platforms that already understand the complexity of these environments.

This is one reason vertical SaaS businesses operating in regulated sectors often prove particularly resilient.

Generic software tools which operate horizontally across industries are typically the most exposed to disruption.

By contrast, companies that build deep industry expertise, understanding sector workflows, regulations, integrations and customer behaviours, develop much stronger foundations.

This is one reason vertical SaaS businesses have historically achieved higher valuation multiples than horizontal tools.

In an AI-driven world, that advantage may widen further.

Domain knowledge combined with sector data creates a powerful competitive moat.

Some software companies become difficult to replace simply because of how many systems connect through them.

Platforms that sit at the centre of an ecosystem, integration layers, operational hubs or developer platforms, often become essential infrastructure.

Replacing them does not just mean switching one product.

It means disrupting multiple workflows across an organisation.

AI typically builds on top of these platforms, rather than replacing them.

Perhaps the most important question founders should ask is this:

Does AI weaken your product – or strengthen it?

Software is already moving from:

SaaS 1.0 — tools that help humans’ complete tasks

To
SaaS 2.0 — systems that increasingly perform those tasks themselves.

Companies designing their platforms around this shift, embedding automation, AI-driven workflows and outcome-based value, are positioning themselves for the next generation of software.

In many cases, AI does not reduce the value of the platform.

It multiplies it.

Despite the noise around AI disruption, this is not a story about software disappearing.

It is a story about software evolving.

The companies most likely to succeed will be those where data, domain expertise and deep integration create real defensibility, and where AI becomes a driver of value rather than a threat to the model.  SaaS companies that can capitalise on this have a strong opportunity for growth and value creation in the age of AI.

For founders building today, the key question is not whether AI will reshape software.

It already is.

The real question is:

How will your product evolve alongside it?