📊 Full opportunity report: The runway.How enterprise-revenuelock becomes the load-bearing valuation argument. on ThorstenMeyerAI.com — validation score, market gap, and execution plan.
TL;DR
OpenAI and Anthropic are launching historic IPOs with valuations based on enterprise revenue lock, not profitability. This shift emphasizes the importance of enterprise contracts in AI valuation models.
OpenAI and Anthropic are both preparing to launch initial public offerings in 2026, with valuations exceeding $900 billion, driven primarily by their enterprise-revenue lock rather than profitability.
OpenAI is targeting a valuation near $1 trillion, with an S-1 filing expected in the fourth quarter of 2026. It generates approximately $25 billion annually, with over 40% of revenue from enterprise clients, but faces projected losses of around $14 billion in 2026. Anthropic aims for a valuation above $900 billion, with a $30 billion annualized revenue run rate by April 2026, mainly from enterprise customers contributing about 80% of its revenue. Both companies are investing heavily in compute capacity, with long-term commitments in the hundreds of billions of dollars.
Despite high revenues, neither company is profitable; OpenAI’s gross margin is near 33%, while Anthropic reports around 40%, with internal forecasts suggesting margins could reach 77% by 2028. The valuations are based on revenue multiples—up to 40x—relying on the assumption that enterprise lock will sustain high valuations even before profitability is achieved. Critics, including Goldman Sachs’ Greg Jensen, suggest these multiples are “priced for a monopoly outcome that does not yet exist.”
The runway.
How enterprise-revenue
lock becomes the load-
bearing valuation
argument.
a multiple no incumbent commands
OpenAI racing 40% → parity
forecast the valuation requires
not cash-flow positive before ~2030
$1T target ÷ ~$25B
run-rate revenue
>$900B reported ÷
~$30B run rate
OpenAI gross margin ·
95% of users are free
- ~80% enterprise revenue from the start
- Claude Code >$2.5B, 54% of the coding-tool segment
- ~40% margin today, 77% forecast by 2028
- Ad-free · PBC + Long-Term Benefit Trust
- Risk: a single-product (Claude Code) concentration
- 900M weekly users · enterprise 40% → parity
- Subscriptions + API + ads pilot + government
- Deployment Company >$4B + Tomoro acqui-hire
- The brand name for AI · broadest distribution
- Drag: consumer margin it is racing to offset
compute-burdened
by 2028 ·
inference cost
must fall
the valuation requires it
The runway is the time between the compute bill and the margin that pays it. The IPO is the refueling. And the enterprise lock is the bet that the disruption the agents are causing will, before the runway ends, become an annuity durable enough to justify the largest valuations ever assigned to companies that have never turned a profit.Thorsten Meyer · The Runway · Enterprise Reorg 04
Why Enterprise Revenue Lock Is the Key to Valuation
The focus on enterprise revenue lock as the core valuation argument indicates a shift in how AI companies are valued in public markets. This approach emphasizes contracted, embedded, and expanding enterprise contracts as a safeguard for high multiples, contrasting with consumer-focused models characterized by thin margins and uncertain retention. The IPOs will test whether enterprise lock can justify valuations that surpass traditional software companies, potentially reshaping industry standards and investor expectations.
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The Rise of AI Valuations Based on Enterprise Contracts
Over the past three years, AI labs like OpenAI and Anthropic have transitioned from primarily consumer-facing models to emphasizing enterprise adoption. OpenAI’s GPT models are now integrated into business workflows, with enterprise revenue surpassing consumer sales by late 2026. Similarly, Anthropic’s focus on enterprise clients has driven its revenue growth and margin improvements. Both companies are investing heavily in compute infrastructure, betting that enterprise lock will sustain high valuations and fund future development.
This shift reflects a broader industry trend where the valuation of AI companies increasingly depends on their ability to embed their technology within enterprise workflows, rather than relying solely on consumer usage or ad-based revenue models.
“The enterprise-revenue lock is being asked to do something a consumer-subscription business cannot do — justify a mega-cap multiple on a company that loses billions and has never been profitable.”
— Thorsten Meyer
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Uncertainties Over Margins and Profitability
It remains unclear whether the margins necessary for these enterprise contracts to generate durable, profitable revenue will materialize at the levels projected. Both companies are investing heavily in compute capacity, which could erode margins before revenues turn profitable. The actual profitability and sustainability of the enterprise lock are still unproven, and the upcoming IPO disclosures will be critical in testing these assumptions.
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Upcoming IPO Filings and Market Testing of Enterprise Lock
In the coming months, OpenAI and Anthropic are expected to file their S-1 documents, which will include detailed financial disclosures and projections. Market reception will determine whether the enterprise-revenue lock can sustain high valuations amid questions about margins and profitability. The first quarter of public trading will be a key milestone in validating the industry’s reliance on enterprise contracts as the primary valuation driver for AI companies.
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Key Questions
Why are enterprise revenue figures so important for these IPOs?
Enterprise revenue figures are seen as more durable and predictable, making them a more credible basis for high valuation multiples compared to consumer usage, which is often thin-margin and uncertain.
Can enterprise lock truly justify the high valuations being projected?
This remains uncertain. While enterprise contracts provide a steady revenue stream, margins and long-term retention are still unproven, and the upcoming disclosures will be crucial in assessing their validity.
What risks do these valuations pose to investors?
The primary risks include margin erosion due to compute costs, failure to achieve projected profitability, and the possibility that enterprise lock does not deliver the expected valuation support.
How does this shift affect the broader AI industry?
It signals a move toward valuing AI companies based on their embeddedness in enterprise workflows and contracts, potentially setting new standards for valuation and investor expectations in the sector.
Source: ThorstenMeyerAI.com
