How AI Is Rewriting the Rules of the Software Business Model

For over a decade, SaaS dominated the software industry playbook. Build a useful tool, price it per seat or by usage, deliver it through the cloud, and scale through sales and CS. It worked. But that model is now being challenged, not just by better products, but by a new kind of software entirely: AI-native agents.

This isn’t just a technology wave. It’s a fundamental rewiring of the software business model.

From Tool to Agent

Traditional software was an assistant. You used it to work more efficiently, but it didn’t replace the human doing the task. With agentic AI, that boundary is being crossed. AI agents are no longer assistants. They are operators. A customer support AI can now autonomously handle 70% of tickets. A legal AI can review contracts. A financial AI can reconcile statements. The software isn’t just enabling work anymore. It’s doing it. This shift turns software from a utility into an active performer. That means the way we charge for it needs to evolve too.

Outcome-Based Pricing Is Emerging

If an AI agent does the work, why charge for access? Why charge per user? The logic flips.

Companies like Sierra are pioneering outcome-based pricing. If the AI resolves the issue, it gets paid. If it fails and escalates to a human, it's free. That’s a radically aligned model, one where vendors get paid when value is created.

It’s not trivial to implement. You need deep integration, metrics, and trust. But it’s closer to how real-world services work: performance-based contracts. And it could become the new default for software that works autonomously.

Consulting Is Getting Productized

Agentic AI is quietly doing something else: it’s eating into professional services. What used to require a team from a consulting firm can increasingly be delivered through a finely tuned AI agent.

A good AI product today is part software, part service. It carries domain knowledge. It adapts to the user. And it improves over time. That’s very different from shipping static tools and training customers on how to use them.

This trend is strongest in areas like legal, compliance, finance, and customer ops - domains where expertise is repeatable and data is rich. The productization of consulting is real, and AI is the delivery mechanism.

Moats Are Shifting to Data and Workflow

In the SaaS era, product design and GTM execution were the edge. In the AI era, proprietary data, contextual feedback, and tight workflow integration are the new moat.

Everyone can access the same models. What you feed them, and how you close the loop, is what matters now.

Vertical AI plays, built deeply for a specific industry with access to unique datasets and workflows, are positioned to lead. That’s why general-purpose AI platforms struggle to differentiate, while niche domain agents thrive.

Incumbents vs Startups: Who Has the Edge?

Historically, startups had the advantage. They weren’t held back by old infrastructure or outdated pricing models. And that’s still true. Startups can build AI-native software from scratch, price around outcomes, and move quickly.

But this time, incumbents have the data. They have years of operational context, deep customer histories, and domain expertise, all of which are critical to building a high-performing AI agent.

The likely winners are those who collaborate. Startups bring the models, speed, and clarity. Incumbents bring distribution, data, and trust. The real advantage lies in the nexus, where agility meets depth.

The Next Software Giants Will Deliver, Not Just Assist

Agentic AI isn’t just a new feature. It’s a new model for what software is. The best AI products won’t just make your team more productive. They’ll be part of your team.

That changes everything, from how you build to how you sell to how you get paid.

So if you're building for this next era, ask yourself:

• What job can we take over entirely?

• How do we guarantee performance?

• And how do we price based on the actual value we deliver?

That’s the bar now. And the ones who meet it will define the next chapter of enterprise software.