The massive CapEx from companies like Alphabet and Amazon isn't just to compete in the existing software market. The scale of investment only makes sense when viewed as an attempt to capture a significant portion of the $6 trillion U.S. white-collar labor market through automation.

The primary economic incentive driving AI development is not replacing software, but automating the vastly larger human labor market. This includes high-skill jobs like accountants, lawyers, and auditors, representing a multi-trillion dollar opportunity that dwarfs the SaaS industry and dictates where investment will flow.

For AI companies experiencing explosive growth like Harvey (tripling ARR in a year), traditional TAM analysis is an obstacle, not a tool. Such growth signals the company is capturing a new budget pool (e.g., labor costs) that dwarfs the existing software market. In these cases, the revenue trajectory itself becomes the best indicator of the true TAM.

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 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.

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.

Elad Gil argues that the total addressable market for AI companies is not limited to traditional seat-based software pricing. Instead, it encompasses the multi-trillion dollar human labor market that AI can augment or automate.

The massive investment in AI seems disproportionate to the software market's size. However, its true potential is in automating and augmenting the services industry, which is 25 times larger than software, thus justifying the spend.