The guest argues that a specific AI vertical is underinvested: automating administrative knowledge work that is fundamental to how companies get paid. These tools have high revenue durability as they become core financial infrastructure, yet receive less VC attention than other AI categories.

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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.

Most companies are not Vanguard tech firms. Rather than pursuing speculative, high-failure-rate AI projects, small and medium-sized businesses will see a faster and more reliable ROI by using existing AI tools to automate tedious, routine internal processes.

The economic incentive for VCs funding AI is replacing human labor, a $13 trillion market in the US alone. This dwarfs the $300 billion SaaS market, revealing the ultimate goal is automating knowledge work, not just building software.

VCs have traditionally ignored the massive $16T services sector due to its low margins. AI automation can fundamentally change this by eliminating repetitive tasks, allowing these companies to achieve margin profiles similar to software businesses, thus making the sector newly viable for venture investment.

While AI can improve existing software categories, the most significant opportunity lies in creating new applications that automate tasks previously performed by humans. This 'software eating labor' market is substantially larger than the traditional SaaS market, representing a massive greenfield opportunity for startups.

Unlike SaaS which sells to limited software budgets (e.g., 1% of revenue), vertical AI agents automate core business functions. This allows them to tap into much larger operational and labor budgets. Companies can capture 4-10% of a customer's total spend by replacing expensive human-led tasks like customer support.

The most durable AI applications are those that directly amplify their customers' revenue streams rather than merely offering efficiency gains. For businesses with non-hourly billing models, like contingency-based law firms, AI that helps them win more cases is infinitely more valuable and defensible than AI that just saves time.

Thrive Capital invested in an AI-powered accounting firm, not an accounting AI software tool. Their thesis is that in some industries, the service provider who uses AI to become hyper-efficient will capture more value than software vendors selling tools to a fragmented customer base. This is a bet on the business model, not just the technology.

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.

Unlike traditional software that supports workflows, AI can execute them. This shifts the value proposition from optimizing IT budgets to replacing entire labor functions, massively expanding the total addressable market for software companies.