The Inference Economy: The Missing $800 Billion Isn't Missing

Why orchestration revenue from labor market capture will generate trillion-dollar infrastructure returns.

Credit: A.C.

The AI infrastructure build-out faces a perceived $800 billion revenue gap by 2030, per Bain & Company’s 2025 Technology Report. This analysis is arithmetically sound but strategically wrong. The missing revenue will emerge from a significant economic transition: AI systems capturing value directly from the $60 trillion global labor market rather than from IT budgets. As agentic colleagues perform cognitive work, enterprises will pay for tasks and outcomes rather than software licenses. This creates “orchestration revenue” priced at multiples of underlying inference costs, with those compute costs flowing directly back to infrastructure providers. Every completed workflow generates billable compute consumption that cascades through the value chain to hyperscalers and chip manufacturers. This produces gross margins of ~60-90% for orchestration platforms, while simultaneously generating the predictable, high-margin infrastructure revenue needed to justify today’s build-out.