📊 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 preparing for historic IPOs, emphasizing enterprise revenue as the main valuation pillar amid skepticism about margins and profitability. The move highlights how enterprise lock is shaping AI industry valuations.
OpenAI and Anthropic are preparing for some of the largest IPOs in history, with valuations potentially exceeding $900 billion. Both companies are emphasizing enterprise revenue as the core justification for their high valuations, amid ongoing skepticism about profitability and margins.
OpenAI is expected to file an S-1 in the fourth quarter of 2026, targeting a valuation near $1 trillion, with revenue around $25 billion annually and a projected loss of $14 billion in 2026. Anthropic is in talks to raise over $900 billion, with a potential IPO as early as October 2026, and has reported an annualized revenue of over $30 billion, with 80% coming from enterprise clients.
Both companies are sitting on massive compute commitments and are not relying on consumer revenue to justify their valuations. Instead, they are positioning enterprise contracts—contracted, embedded, and expanding—as the foundation for their high multiples, despite concerns about margins and profitability. Industry experts note that these valuations are driven by a belief that enterprise lock will sustain long-term value, even as margins remain uncertain.
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 Lock Is Central to AI Valuations
This development underscores a shift in how AI companies justify their sky-high valuations. By emphasizing enterprise revenue, these labs aim to demonstrate durable, contracted income streams that can support multiples far above traditional software firms. The move also reflects a strategic effort to convert industry disruption into a measurable, monetizable asset, even as skeptics question whether margins will materialize as expected.
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Background of AI IPOs and Enterprise Revenue Focus
Over the past year, OpenAI and Anthropic have grown rapidly, with revenue surging due to enterprise contracts and expanding AI agent deployments. Despite their impressive top-line figures, both face skepticism about profitability, with OpenAI projected to lose billions annually and margins remaining thin. Industry insiders note that the high valuations are based on the assumption that enterprise lock will translate into sustainable, high-margin revenue streams, a hypothesis now being tested through their upcoming IPO filings.
“The core of these IPOs is the enterprise lock—contracted, embedded revenue—that is being positioned as the load-bearing argument for the valuation multiples.”
— Thorsten Meyer
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Unclear Whether Margins Will Materialize at Scale
It remains uncertain whether the margins promised by the enterprise lock will materialize as projected. OpenAI’s gross margin is near 33%, with internal forecasts aiming for 77% by 2028, but these targets are aggressive. Similarly, Anthropic’s margins are reported around 40%, but whether they can sustain or improve these levels amid high compute costs is still unclear. The upcoming IPO filings will likely include disclosures that test these assumptions.
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Next Steps: IPO Filings and Margin Disclosures
Both OpenAI and Anthropic are expected to file their S-1 documents in late 2026, which will include detailed financial disclosures and margin forecasts. These filings will serve as a test of whether the enterprise revenue and margin assumptions underpinning their valuations hold up under scrutiny. Industry observers will closely analyze the disclosures to assess the sustainability of their valuation strategies.
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Key Questions
Why are enterprise revenues so important for these IPOs?
Enterprise revenues are viewed as more stable, contracted, and embedded in workflows, making them more attractive for supporting high valuation multiples despite high losses and thin margins in consumer segments.
What risks do these companies face in relying on enterprise lock for valuation?
The main risk is that margins may not materialize as expected, and enterprise contracts could be disrupted or not expand as anticipated, threatening the sustainability of their high valuations.
How do the margins of OpenAI and Anthropic compare?
OpenAI’s gross margin is near 33%, with internal targets of 77% by 2028, while Anthropic reports around 40%, with internal forecasts aiming for 77%. The actual margins at scale remain uncertain and will be scrutinized in upcoming disclosures.
What does this mean for the future of AI industry valuations?
This marks a shift toward valuing AI companies based on their enterprise contracts and embedded revenue streams, which could set a new standard if these models prove sustainable and profitable.
Source: ThorstenMeyerAI.com
