AI's Total Addressable Market

Why AI is far bigger than most people think
January 27, 2025
AI Tam The total market size (TAM) for AI is a combination of two (2) primary components:
  1. The total cost of human workforces
  2. The amount of money that current and future companies will pay to start, 10x, or 1000x their business

We're talking hundreds of trillions of dollars.

Don't get distracted.

EDIT: June 1, 2026

The way I've been thinking about this for the last 18 months or so is this instead:

1. The TAM is actually *decision support for Earth

So in other words, there are trillions of decisions being made every minute on the planet. From individuals, to families, to communities, to cities, to states, to countries, etc. Both personally, and also for all businesses.

Most entities would like to make better decisions. So that's the opportunity.

2. The TAM is the delta between current and ideal state for all entities

Another way I frame this is to say that there is always a gap between the current state and ideal state for any entity, both personal and professional.

And the ultimate instantiation of AI is the continuous elimination of that delta.

So ultimately I think it's #2. Something like:

The ultimate opportunity for AI technology is the elimination of delta between Current State and Ideal State for all entities.

That means using AI to continuously:

  1. Deeply understand current state
  2. Collect and nurture the desired ideal state
  3. Work to reduce the distance between the two

We could call that Decision Support as in #1, but I think it's more accurate and precise to frame it as the decisions required to move towards Ideal State.

supporting = loving

For 29.6307 years I've been creating ad-free technical tutorials and essays here. 3,055 pieces and counting.

It's a one-person effort that's also my livelihood. If it makes your day easier or more pleasant in any way, please consider supporting the work with a monthly or one-time donation.

It helps me make more content, and is deeply appreciated as well. 🫶🏼