As AI inference costs soar, the next infrastructure boom depends on tapping 3 billion idle PC GPUs worldwide. Shifting lighter tasks like local copilots from massive data centers to consumer machines can slash delivery costs and latency, widening the overall AI market. Nvidia reported $81.6 billion in revenue in its latest quarter, with $75.2 billion coming from data centers. CEO Jensen Huang described the buildout of AI factories as “the largest infrastructure expansion in human history.” Roughly 3 billion PC-based GPUs are already sitting inside consumer and prosumer machines, and only a small share of that installed capacity is being used for AI work. McKinsey expects inference to surpass training by 2030 and represent more than half of all AI compute in data centers. OpenAI generated $13 billion in revenue in 2025 while holding expenses to about $8 billion, and projects roughly $50 billion in computing-power spending in 2026 alone. HSBC estimates suggest the company could still lose about $14 billion that year and need to raise at least $207 billion by 2030 to keep absorbing losses driven by soaring compute costs.