AI Ledger Hepburn Advisory Hepburn Advisory

Revenue Ledger

Data refreshed:

AI-specific revenue by buyer segment, channel, provider, and cost outcome.

Revenue Flow

Scroll horizontally to explore the Sankey, or rotate to landscape.

Provenance tier: 1 Sourced (A = first-party disclosure, B = corroborating sources) 2 Derived (A = deterministic calc from Tier 1, B = triangulated) 3 Projected (A = anchored extrapolation, B = interpolated, C = scenario assumption) 4 Editorial (replace ASAP) — hover any node for source citation
? Why do the middle columns shrink? Each column shows the dollars that flow through it. Channels (Hyperscalers, Trad. SaaS) retain a margin before passing revenue to Model Providers — Hyperscalers clip ~20%, Trad. SaaS ~60%. That retained margin flows directly to Generated Cashflow (bottom right), bypassing Model Providers entirely. So each column is smaller than the one before it — the drop is the channel margin.
i Per-archetype channel routing. Each provider's revenue routes to channels per its entity archetype — frontier labs send ~95% of API revenue direct (5% via hyperscaler resale); AI Natives ~90% direct; Enterprise SaaS ~50/50. The Who Pays column splits AI buyers into AI Natives (heavy API consumers like Cursor / Glean / Perplexity) and Enterprises & Govs (Fortune 500, regulated, sovereign). See methodology § entity archetype taxonomy.
! Scope. The Revenue Sankey shows model providers earning AI-attributable customer revenue in the year. Labs that don't directly monetise their models — Meta (Llama, open-weight, ad-funded indirectly) is the canonical example — are excluded. Their AI spend appears on the Capital Ledger (capex) and Compute Ledger (chip purchases) instead.
Click or hover a node to see flow details and tier provenance

What Would Have to Be True

Convergence signals that would confirm or disconfirm the revenue trajectory in the selected year. Each signal has a defined threshold and a current observed value.