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It used to be that if you invested in SaaS, you slept well at night. Returns were predictable because the business model was subscription-based and incredibly scalable: build a horizontal cloud-based platform to target as wide a market as possible, charge per seat and grow by expanding the user base.

1, and their peers returned billions to investors on that model. But now, due to AI, where AI agents are replacing humans as the user (through what the industry calls 鈥渉eadless鈥� models) and upending the per-seat model, the SaaS market has lost its predictability. January’s $300 billion single-session wipeout is a leading indicator that the old SaaS model has passed its peak.

Investors are retrenching and trying to predict what鈥檚 next as the three frontier AI companies vault into the public markets at multitrillion-dollar valuations. We would argue that these infrastructure platforms enable the next wave of software innovation: AI-native software that automates and enables the $2 trillion white-collar services market.

Generic, horizontal SaaS, as we know it, is a declining legacy model (like on-premise software before it), but investors still have reason to be optimistic about the software market. That鈥檚 because AI-native software is going after a much larger opportunity than SaaS ever claimed and the productivity gains and value creation opportunities are unprecedented. The target markets are vertical industry focused and highly specialized, priced differently and built on proprietary data moats that didn’t exist five years ago.

Death of per-seat pricing

SaaS has always been priced on a per-seat basis. That model evaporates the moment AI agents generate most of the usage. A company that once needed 100 CRM licenses for its sales operations team may soon need just 50.

Technology companies facing that reality have to choose a new path forward beyond connecting people鈥檚 workflow: perform and charge for the actual work done (usage) or based on outcomes (ROI). A legal AI platform charges per contract drafted, doing the work of a lawyer. Here the software charges for some fraction of the labor it replaces. A spend management AI-native software application can take a percentage of overages found or a chargeback software application could take a fee on the value of the chargebacks it successfully recovers.

The next era of AI-native software runs on automation and performing knowledge-worker actions, not connecting workers or workflows. These solutions reach beyond IT budgets to much larger labor budgets. The companies that adapt will build faster, deliver more value and command a premium for it.

Horizontal is a liability

Generic horizontal SaaS is the most vulnerable to this changing market. If an entire product is a wrapper around a workflow that an AI agent can now handle autonomously, the value proposition may be greatly reduced. Form builders, project management platforms, SMB-focused CRMs, off-the-shelf social schedulers: these categories are compressing fast and may not recover.

The defensible positions now belong to vertical niche specialists, companies that have built what we call the three 鈥淒s.鈥� Distribution through a recurring and longstanding customer base.

Domain expertise specialized to operate in regulated or complex industries. Proprietary data that drives decision-making and is closely held by customers and inaccessible to frontier models.

When your product is built around the specific workflows, terminology and compliance requirements of one industry, ending a vendor relationship is less about migrating data and more about rebuilding a complex web of experiences, corner cases and historical knowledge. Customers stay not because they’re trapped, but because the cost of retraining, reconfiguring and finding a vendor who understands their world is too high.

The more deeply a company understands the regulatory environment, the operational constraints, and the institutional logic of a specific industry and a specific customer, the harder it becomes to displace.

Legal contract repositories, insurance underwriting criteria, bank loan performance data; once embedded in a model and a workflow, these assets create high switching costs that dwarf anything a generic SaaS contract ever produced. You can export a Salesforce contact list. You cannot export your underwriting logic.

People are part of the product

The model that will define the next decade of B2B software deliberately combines software and services, what practitioners call Human-in-the-Loop, or HITL: pairing agentic intelligence with human judgment at the points in a workflow where it matters most.

Legal, healthcare, cybersecurity, construction, financial services, defense; these verticals are defined by high stakes, regulatory complexity and contextual judgment. Routine and repetitive tasks may be mostly automated, but some portion of decisions will always require human judgement because the cost of errors or omissions is prohibitive.

This solutions-centric customer relationship changes what a software company fundamentally is. When a vendor is embedded in how a client operates, handling onboarding, workflow design, optimization and quality control, it accumulates something pure SaaS rarely achieved: proprietary data, domain expertise and institutional trust. Every client engagement makes the product smarter and each deployment deepens the moat.

This is why the most durable software businesses of the next decade will be built inside verticals, not across them. The companies that understand this will stop treating services as a cost of implementation and start treating them as a compounding asset.

A bigger market than SaaS ever was

Even capturing a small fraction of what projects is a $6 trillion annual productivity opportunity from AI transformation dwarfs the traditional enterprise software market. AI-native vertical platforms no longer just compete for the technology budget, they also compete for the labor budget, the compliance budget and the risk budget. That’s a much bigger pie and a more strategic partnership conversation than any per-seat SaaS vendor ever got to have.

The winners won’t be companies that bolt AI onto existing SaaS products, or that add a services layer as an afterthought. They will be the firms with true subject matter expertise that happen to run on AI-native software. They will collapse the boundary between software and services entirely, building businesses whose value compounds with every customer relationship and every data asset they accumulate.

The AI-native software company is a fundamentally different kind of company than the SaaS era ever produced. And it’s worth considerably more.

is the founder, managing partner and chair of the investment committee at . He launched Lateral with a strategy to allocate first institutional growth capital to independent, owner-operated middle-market businesses underserved by typical buyout firms. Previously, he served as a managing director at , a venture capital and growth equity firm that has invested in more than 300 companies including , , , , and . De Silva also previously co-founded , a marketplace for construction equipment that was sold to for nearly $800 million. He received an MBA from , a master of philosophy from the , and an undergraduate degree from .

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