Historically, payroll has dominated corporate expenses. As AI automates knowledge work previously done by humans, a significant portion of the budget will shift. Spend on SaaS, APIs, and model usage will grow from a small percentage to a major line item, displacing traditional labor costs.

Mamoon Hamid views AI's true market size not as a software category, but as a portion of the $60 trillion global labor market. Frontier models sell "units of labor," which is why companies like Anthropic can scale revenue so rapidly by tapping into a much larger pool of value.

The AI market is moving beyond simple $20/month subscriptions toward high-cost API consumption. As AI's value becomes clearer, companies are increasingly willing to approve massive budgets, with figures like $250,000 per engineer per year for AI inference becoming a justifiable business expense.

AI platforms like Anthropic and OpenAI are seeing unprecedented revenue growth because they're augmenting and competing with human labor costs. This is a far larger market than traditional IT budgets, enabling multi-billion dollar revenue months.

The $15-$25 per-review price for Anthropic's tool moves AI expenses from a predictable monthly software subscription to a variable cost that scales like human labor. This forces CTOs to justify AI budgets with direct headcount savings, creating immense pressure on ROI.

Historically, software engineering required minimal capital—a laptop and internet. AI development now mirrors heavy industry, where the capital asset (like a $10M crane or $100M cargo ship) costs far more than the skilled operator. An engineer's compute budget can now dwarf their salary, changing team economics.

A massive budget shift is underway where companies spend exponentially more on AI agents than on foundational software like CRM. One small team spends $500k annually on AI agents versus just $10k on Salesforce, signaling a tectonic shift in software value and spending priorities.

Heavy use of AI agents and API calls is generating significant costs, with some agents costing $100,000 annually. This creates a new financial reality where companies must budget for 'tokens' per employee, potentially making the AI's cost more than the human's salary.

Illustrating a dramatic shift in operational expenses, AI company Mercor now spends more on API tokens for its internal agents than on employee salaries. This is a leading indicator for how most enterprises will operate within five years, where compute costs will eclipse human capital costs.