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.

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.

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.

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.

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.

VC Joe Lonsdale argues investors are overly focused on software 'infinity stories' that could be worth trillions. Meanwhile, the 'real economy' (construction, quarrying, manufacturing) represents 85% of capital and is ripe for AI-driven transformation. These less-hyped applications represent a massive, misunderstood, and less competitive investment area.

The AI investment case might be inverted. While tech firms spend trillions on infrastructure with uncertain returns, traditional sector companies (industrials, healthcare) can leverage powerful AI services for a fraction of the cost. They capture a massive 'value gap,' gaining productivity without the huge capital outlay.

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.