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.

For capital-intensive AI companies like Meta, layoffs are driven by a new financial reality: the need to reallocate massive budgets from employee salaries to compute infrastructure. The enormous cost of GPUs means companies literally cannot afford both a large workforce and the necessary AI hardware.

Software companies are using AI tools internally to boost employee productivity. This means future operating expense (OpEx) growth may depend less on the high cost of hiring talent and more on the cost of compute, which is trending downwards. This represents a fundamental shift in the industry's cost structure.

Historically, labor costs dwarfed software spending. As AI automates tasks, software budgets will balloon, turning into a primary corporate expense. This forces CFOs to scrutinize software ROI with the same rigor they once applied only to their workforce.

The explosive AI revenue growth stems from corporations re-categorizing the spending. It's no longer a line item in a constrained IT budget but a strategic investment in labor augmentation and replacement. This unlocks a vastly larger pool of capital from operational budgets, fueling hypergrowth.

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.

Cost savings from AI-driven productivity are not just boosting profits or going to shareholders. Companies are redirecting that capital to buy their own GPUs and TPUs, vertically integrating their tech stacks. This trend represents a major capital rotation from software and headcount into owning the underlying hardware infrastructure.

The huge CapEx required for GPUs is fundamentally changing the business model of tech hyperscalers like Google and Meta. For the first time, they are becoming capital-intensive businesses, with spending that can outstrip operating cash flow. This shifts their financial profile from high-margin software to one more closely resembling industrial manufacturing.

Goldman's CIO predicts that while unit cost per token will decrease, the explosion in token usage from agentic systems will make total AI compute a major corporate expense. He suggests it should be compared to personnel costs, not traditional IT spending.