Unlike traditional B2B markets where only ~5% of customers are buying at any time, the AI boom has pushed nearly 100% of companies to seek solutions at once. This temporary gold rush warps perception of market size, creating a risk of over-investment similar to the COVID-era software bubble.

During a fundamental technology shift like the current AI wave, traditional market size analysis is pointless because new markets and behaviors are being created. Investors should de-emphasize TAM and instead bet on founders who have a clear, convicted vision for how the world will change.

Investors must recognize that S-curve forecasts are not static. Whale Rock initially modeled cloud computing as a $300B deflationary market (versus $600B in traditional IT spend) but later realized it was a full $600B market as it spurred new demand, significantly extending the investment runway.

Successful AI products like Gamma and Cursor don't just add a feature; they create so much value they can charge orders of magnitude more than legacy alternatives. This massive Total Addressable Market (TAM) expansion, not a simple price bump, is the engine of their explosive growth.

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.

For venture capitalists investing in AI, the primary success indicator is massive Total Addressable Market (TAM) expansion. Traditional concerns like entry price become secondary when a company is fundamentally redefining its market size. Without this expansion, the investment is not worthwhile in the current AI landscape.

Companies like Amazon (from books to cloud) and Intuitive Surgical (from one specific surgery to many) became massive winners by creating new markets, not just conquering existing ones. Investors should prioritize businesses with the innovative capacity to expand their TAM, as initial market sizes are often misleadingly small.

When a new, superior technology paradigm emerges (e.g., cloud software), it doesn't just compete with the old one (on-premise). It grows the entire market by an order of magnitude. This principle suggests Databricks could be 10 times bigger than Oracle.

Investors err when they size a new market based on its predecessor (e.g., Uber vs. taxis). A fundamental supply-side change creates new capabilities that unlock massive, previously invisible demand, making initial market size calculations dangerously conservative.