Tracking the spend and revenue of frontier AI companies (May 2026). “WHY I BUILT THIS

• Many industry experts and companies claim AI profitability by 2030 is possible, so I wanted to see how close we really are. This site tracks cumulative spend versus revenue across most major AI companies in one place, allowing you to see exactly how much money is flowing into the industry and how far it is from breaking even.
• I’ll be updating these numbers monthly as new reports and financials drop. Perhaps one day, the big “NO” will become a “YES,” and the question will finally be answered :). So far? The big winner is NVIDIA, who is receiving huge profits from the AI boom by positioning itself as the primary chip supplier to the AI sector.

• All figures are estimated cumulative totals (all-time). Because most of these companies are private, the numbers aren’t exact; instead, they are built from leaked financials, SEC filings, earnings calls, and industry estimates from sources like Bloomberg, the WSJ, The Information, and Epoch AI (all referenced at the bottom). The punchline ‘EVERYONE IS BROKE’ is intentionally punchy, but shouldn’t be taken absolutely literally.
• The site includes both, big tech infrastructure spend and pure lab spending, hence why companies like Amazon and Google have huge spend figures compared to the pure labs like OpenAI or Anthropic (big AI investments, not much direct AI revenue yet). It’s important to note that the site tracks whether AI investment specifically has broken even yet, not company-wide profitability, hence why companies such as Amazon and Google look so far in the red despite being hugely profitable companies as a whole.
• Spend numbers include direct R&D costs, compute, and capital expenditure on AI infrastructure (data centres, chips, and networking). Capex is treated as spend despite having long-term asset value; this is intentional. The framing shows the sheer scale of capital being committed to AI before returns materialise, rather than smoothing it across a depreciation schedule. Indirect AI revenue (E.g. Google Search performance boosted by AI Overviews, or Microsoft Office revenue lifted by Copilot) is excluded because there is no reliable way to attribute what share of those gains AI is actually responsible for. The $/sec counters use current annual burn rates rather than historical averages, to reflect what’s happening right now.
• Revenue numbers are the trickiest to estimate due to a lot less information on them being readily available. Thus, the revenue figures here are mostly estimated and extrapolated off of ARR figures. Currently, I’d say these numbers are more optimistic than anything, but I will be refining this over time as more information comes out…”