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As large AI models absorb functions of traditional SaaS products, investors and entrepreneurs are shifting focus back to tech-enabled services. Integrating AI deeply into physical services and workflows is now seen as creating more defensible, lasting value than pure software, reversing a years-long trend.

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Industries with historically low software adoption (like trial law or dentistry) are now viable markets. Instead of selling a tool, AI startups are selling an outcome—the automation of a specific labor role. This shifts the value proposition from a software expense to a direct labor cost replacement.

Founders are stuck in a SaaS mindset, selling tools to existing service providers. The bigger opportunity is to build new, AI-first service companies (e.g., accounting, legal) that use AI to deliver a superior end-to-end solution directly to customers.

Pure software-as-a-service (SaaS) companies are vulnerable to being replaced by foundational AI models that can replicate their functionality. A Sequoia partner suggests the defensible model is to become a services company that uses technology as a layer, focusing on implementation, strategy, and human expertise.

Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.

The 'SaaS-pocalypse' narrative is flawed because IT/SaaS is only 8-12% of enterprise spend. Companies will use powerful AI models to create value in the other 90% of their business—like operations and sales—rather than just rebuilding core software like ERPs or CRMs where the financial upside is limited.

AI companies are pivoting from simply building more powerful models to creating downstream applications. This shift is driven by the fact that enterprises, despite investing heavily in AI promises, have largely failed to see financial returns. The focus is now on customized, problem-first solutions to deliver tangible value.

Businesses previously considered non-venture scale due to service-based models and low margins, like Managed Service Providers (MSPs), are becoming investable. By building with an AI-first core, these companies can achieve the high margins and scalability required for venture returns, blurring the line between service and product.

AI is transforming business models by enabling companies to sell software bundled with the actual work it performs. This "work-as-a-service" approach is unlocking historically software-resistant markets like legal and construction, where the value proposition is the completed task, not just the tool.

The fundamental shift from AI isn't about replacing foundational model companies like OpenAI. Instead, AI creates a new technological substrate—productized intelligence—that will engender an entirely new breed of software companies, marking the end of the traditional SaaS playbook.

Traditionally, service businesses lack scalability for VC. But AI startups are adopting a 'manual first, automate later' approach. They deliver high-touch services to gain traction, while simultaneously building AI to automate 90%+ of the work, eventually achieving software-like margins and growth.