ARK Invest’s Brett Winton outlines $30T AI market potential

Think of the global economy’s knowledge workers as one giant payroll. Accountants, analysts, lawyers, consultants, coders, marketers: the people who get paid to think for a living. ARK Invest’s Chief Futurist Brett Winton pegs that collective wage bill at roughly $30 trillion (excluding China), and he believes AI is coming for a meaningful chunk of it.

Winton’s thesis is that AI won’t simply make knowledge workers faster. It will begin to substitute for the work itself, redirecting enormous pools of labor spending toward software and automation.

The numbers behind the thesis

ARK projects that AI-driven software spending could land somewhere between $3 trillion and $7 trillion annually by 2030. For context, the entire global software market today is measured in the low single-digit trillions. ARK is essentially arguing that AI alone could double or triple it within half a decade.

One of the most striking data points in Winton’s framework is the cost curve. AI inference costs on agentic benchmarks have reportedly been declining by more than 99% year over year, a pace ARK expects to persist through at least mid-2026.

Who captures the value

Winton sees frontier model companies as the primary beneficiaries. ARK estimates the potential enterprise value for this cohort at $15 trillion to $20 trillion or more.

OpenAI’s annual recurring revenue is reportedly in the $20 billion to $30 billion range. Anthropic, meanwhile, has been growing even faster than its competitors in recent quarters.

ARK also estimates that compute capacity rents at roughly $10 billion per gigawatt and can monetize output at around $30 billion per gigawatt. For every dollar spent building and powering the data centers that run these models, roughly three dollars of economic value comes out the other side.

The macro case: 7% GDP growth

ARK forecasts that AI could accelerate annual GDP growth to 7%, a figure that sits dramatically above most mainstream estimates. The US economy has averaged somewhere around 2-3% real growth in recent decades.

What investors should watch

For investors, the key variables to monitor are adoption velocity and margin compression. If enterprises adopt AI tools faster than expected, the $7 trillion end of ARK’s software spending range becomes plausible. If competition among model providers drives prices toward zero, the $15 trillion to $20 trillion enterprise value estimate for frontier companies could prove too generous, with value accruing instead to the application layer and end users.

The $30 trillion knowledge-worker wage bill isn’t going to evaporate overnight. But even redirecting 10-20% of it toward software and AI services over the next decade would create one of the largest wealth transfers in economic history.

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