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.

AI enables "software does labor" business models in industries previously deemed too small for specialized software, like dental offices or trial law. By replacing or augmenting specific labor tasks, startups can justify high-value contracts in markets that historically wouldn't pay for traditional SaaS tools.

Before replacing human workers, AI expands the total addressable market by making services economically viable for previously unserved segments. For instance, Intercom customers now offer AI support to their free users, something they could never afford with human agents.

The new generation of AI automates workflows, acting as "teammates" for employees. This creates entirely new, greenfield markets focused on productivity gains for every individual, representing a TAM potentially 10x larger than the previous SaaS era, which focused on replacing existing systems of record.

Companies like Sierra can't justify a 100x ARR valuation by targeting the existing software market (e.g., $8B Service Cloud). The bet is that they will capture a significant portion of the much larger human labor market ($200B+ for support agents). This represents a fundamental transition of spend from human capital to software.

The true market opportunity for AI is not merely replacing existing software but automating human labor. This reframes the total addressable market (TAM) from the ~$400 billion global software industry to the $13 trillion US-only labor market, representing a thirty-fold increase in potential value.

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.

Traditional software automated standardized processes but struggled with complex human interactions like call center support. Generative AI's ability to understand natural language allows software to automate these nuanced tasks, dramatically expanding the total addressable market by tackling problems that were previously impossible to solve with code.

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.