This is FutureSearch's comprehensive forecast of OpenAI's financial future. We have been modeling OpenAI for some time, going back to our first revenue-source breakdown in summer 2024 and our full 2025 OpenAI forecast.
OpenAI confidentially filed its S-1 on June 8, one week after Anthropic, while cautioning that timing is undecided and "it may be a while." Taking that at face value, my central estimate is that OpenAI will IPO around late March 2027 (about a one-in-three chance of a 2026 listing), ARR reaching $42B by mid-2027 (from roughly $25B today), 2026 GAAP losses landing at $25-26B (about 80% above the widely cited $14B non-GAAP figure), and expected 90-day-post-IPO market cap is $0.86 trillion. That is almost exactly the current private mark, so our view is that private markets are calibrated.
But our conclusion comes from weighting an 80% likely scenario where OpenAI does not have the clearly best model or products during this time, and a 20% scenario that they retake the lead in model intelligence and products that they had for most of 2022-2024.
Weighted post-IPO valuation
The chart above conditions the post-IPO market cap on whether OpenAI ships a step-change capability release before the IPO. In the 20% step-change case, the median 90-day market cap is $1.4 trillion. In the 80% no-step-change case, the median is $720 billion, about 15% below the last private mark. Probability-weighted, the expected value is $860 billion. There is no free money for IPO investors.
Common framings of OpenAI's IPO position get this wrong in both directions. The capability gap is wider than bullish reads imply. Anthropic's Mythos already leads 17 of 18 benchmarks (R&D World) and ships into a structure that makes the four-week sustained leadership window nearly impossible to clear. And the loss is worse than bearish reads imply. Q1 2026 actuals annualize to $28 billion in non-GAAP operating loss before you add the $8 billion in stock-based compensation the headline figure ignores.
Start with the valuation math because every other forecast has to clear it. OpenAI raised $122 billion at $852 billion post-money in March 2026 with SoftBank and Microsoft leading the round (CNBC). Both are strategic investors with non-financial motivations: compute access for SoftBank, partnership positioning for Microsoft. Public markets will price on financial returns.
The S-1, confidentially filed on June 8 (CNBC), will show a 35x forward revenue multiple, $25 billion in losses, declining enterprise share, and stalling consumer growth. Bridgewater's Greg Jensen has called this "priced for a monopoly outcome that does not yet exist." I agree.
Step-change here means a model that leads a majority of major AI benchmarks for four consecutive weeks after release. The precedent for the upside scenario is Cerebras, which popped 68% on day one and then gave back 38% over the following 13 days (CNBC). A step-change model would generate more narrative pressure than Cerebras did, but 90 days is enough time for the initial heat to leave.
The precedent for the downside scenario is the mega-IPO that prices to perfection and gets repriced. Facebook traded below its IPO price for a year. Uber traded at roughly half its private peak for two years. OpenAI's S-1 financials, walked through above, sit in that pattern.
Step-change capability timing
The chart above plots the cumulative probability that OpenAI ships a step-change model by a given date. The p50 is June 2028. The p90 is December 2030, effectively "may never happen" for any current IPO investor. By the late-March 2027 median IPO date, only about 20% of the probability mass has accumulated. The later listing buys GPT-6 more runway, which is one of the better arguments for OpenAI taking its time.
The only positive-expected-value position on the IPO is to believe that 20% figure is too low. That is a bet that GPT-6 is transformatively better than current models, and that it holds the lead for four sustained weeks against immediate counter-launches by Anthropic, Google, and xAI. I don't think it does.
GPT-6 reportedly completed pre-training at Stargate Abilene in March 2026 (Nipralo), which puts H2 2026 in launch range. The structural argument against step-change is mechanical, not capability-based. Five labs ship at a roughly six-week cadence. Anthropic demonstrated with Mythos (R&D World) that it can hold a Mythos-class model inside Project Glasswing as a countermeasure. Anthropic can deploy a Glasswing-relaxation variant within days of any OpenAI breakthrough.
Four sustained weeks of unified majority leadership against that response is a much higher bar than a single benchmark sweep at launch. That is what pushes the June 2028 median on the chart out so far past the March 2027 median IPO date. The roughly 20% probability mass accumulated by IPO is the scenario the public market will price into the S-1.
Revenue trajectory
The chart above plots OpenAI's ARR walk through May 2026 and the forecast fan to mid-2027. OpenAI grew from $6 billion to roughly $25 billion ARR over the 17 months to May 2026 (Epoch AI), a run no software company has matched. Growth then flattened: the run rate held near $25 billion from February through April 2026. OpenAI's internal target for mid-2027 is $62 billion. My forecast median is $42 billion (p10 $31B, p90 $60B), about $1.4 billion per month in net new ARR, below the $2 billion-per-month peak and a third short of the internal target. Three reasons it lands there.
OpenAI missed monthly revenue targets in early 2026 (Reuters), and the $2 billion per month peak has not returned. The internal target of $62B requires roughly $3 billion per month in net new ARR for 12 straight months, which is above any monthly figure OpenAI has ever recorded. ChatGPT weekly actives plateaued at around 900 million against a 1 billion target (Where's Your Ed At). The consumer subscription base, which is about 60% of revenue, sits at 50 million paying subscribers.
From here, consumer growth requires either expanding the user base (stalling), raising prices (competitive pressure says no), or upgrading users to higher-priced tiers (real, but limited). And the enterprise segment is leaking. OpenAI's share of enterprise AI spending dropped from about 50% in 2023 to 27-29% in early 2026 (Menlo). Anthropic surpassed OpenAI in new business adoption by April 2026 and now captures 73% of first-time AI buyer spend (Axios). In coding, Anthropic holds 54% to OpenAI's 21%. The enterprise market is expanding fast enough that OpenAI's absolute revenue keeps growing. Its share does not.
The tailwinds are real. The ads business hit $100 million ARR within six weeks of the February launch from 600 advertisers (CNBC) and should land near $2 billion ARR by December. The end of Azure exclusivity in April 2026 opens multi-cloud enterprise distribution for the first time. Neither overrides the consumer saturation dynamic.
CPMs on the ad business have already collapsed from $60 to $15-$35 (Digiday) because only about 2% of ChatGPT prompts involve purchasable products, and the ad tech stack is "primitive" per advertiser feedback (Reuters). Click-through is 0.91-1.3% against Google's 29.2%. The intent on consumer AI prompts is informational, not commercial. Ads scale as a display business that the median chat session cannot monetize at search-grade unit economics.
Loss composition
The chart above stacks OpenAI's widely cited $14 billion non-GAAP loss against the $25-26 billion 2026 GAAP figure I forecast. The headline understates the loss for one reason: it excludes stock-based compensation.
The $14 billion figure comes from internal projections that exclude SBC (The Information). Q1 2026 actuals showed a $6.95 billion non-GAAP operating loss on $5.7 billion in revenue, which annualizes to roughly $28 billion before adding $7-10 billion in SBC. The 2026 GAAP net loss lands around $25-26 billion. The Q1 operating margin was -122%.
That changes the strategic calculus for the $122 billion war chest. At $14 billion per year, the cash covers 8-9 years of runway. At $25 billion per year GAAP, it covers about 5. Profitability by 2029-2030 requires going from -122% operating margin to positive in three to four years while gross margins are squeezed by a smaller share of higher-margin enterprise revenue.
I do not think it happens by 2029. The path to profitability runs through 2031 or later, which the IPO investor base will only tolerate if either revenue compounds substantially faster than I am projecting or model leadership returns. Neither is the base case.
The compute story makes the margin problem worse. OpenAI announced 7+ GW of planned data center capacity through Stargate and adjacent partnerships. As of May 2026, around 0.5 to 1 GW is operational at Abilene (Epoch AI). Data centers take 18 to 36 months from groundbreaking to operational.
About 40% of US data centers planned for 2026 are already delayed (Ars Technica), transformer lead times have stretched to five years in some regions, and OpenAI has already cancelled sites in the UK, Norway, and Lordstown, Ohio (Data Center Dynamics). The 2.2 GW p50 forecast for December 2027 is one-third of the announced plan. Serving $42 billion in revenue on 2.2 GW means either renting third-party capacity at thin margins or unlocking inference efficiency gains that have not been demonstrated. Either path compresses the trajectory to profitability further.
OpenAI increasingly looks like the Google of AI rather than the Microsoft of AI. Like Google in 2005, it has overwhelming consumer reach (900 million weekly actives), a real but capped advertising business, strong brand recognition, and a technology lead that is narrowing rather than widening. Like Google, its durable moat runs through distribution and user habit rather than through technical advantage.
Microsoft's enterprise model produces durable pricing power through deep integration, switching costs, and long-term contracts. OpenAI's enterprise position is actively eroding to Anthropic, multi-model architectures, and open-source price competition. The Microsoft analog is the implicit comparable in OpenAI's current valuation. The Google analog is what the financials actually describe.
This is not bearish on OpenAI as a business. Google became the second most valuable company in history on the consumer-and-ads model. But it does imply a different valuation multiple than the trillion-dollar target. Google trades at about 6x sales and 22x earnings today. OpenAI at $1 trillion against $25 billion of current ARR is at 40x sales, or about 24x on my $42 billion mid-2027 forecast, with undefined earnings. Microsoft trades at about 12x sales and 35x earnings. The current OpenAI valuation prices the Microsoft outcome. The forecasts say the Google outcome is more likely.
Six predictions I'd take the over on, given those forecasts
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The IPO does not happen in 2026, despite Sam Altman's reported September push and Anthropic's late-2026 track (WSJ). OpenAI filed its S-1 confidentially on June 8 and said in the same breath that timing is undecided and "it may be a while." I take them at their word: the filing is queue position, not a commitment, and Sarah Friar's readiness concerns win the internal argument. My median first trading day is March 25, 2027. Probability: 70%.
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The first day of trading goes well, but the 90-day market cap settles near the private mark, not above $1.2 trillion. The IPO premium gets eaten as the S-1 financials filter into institutional models. Probability: 50%.
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GPT-6 ships in H2 2026 but does not clear the four-week step-change bar. It will lead some benchmarks at launch. Anthropic will respond within ten days with a Mythos-derivative GA model or a Glasswing-relaxation announcement that re-fragments the frontier. Probability: 65%.
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The 2026 GAAP net loss lands above $22 billion, and that number is publicly reported for the first time in the S-1. The $14B-vs-$25B gap becomes the central financial narrative for OpenAI's first two public quarters. Probability: 70%.
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OpenAI's share of enterprise AI spend falls below 25% by mid-2027, measured by API-level wallet spend trackers. The CIO-survey number (currently around 56% per a16z) takes longer to fall because of incumbency, but the dollar-share number is the leading indicator and it is already on the floor. Probability: 60%.
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OpenAI's advertising business hits $2.5 to $3 billion ARR by December 2026, slightly above the FutureSearch p50 and roughly in line with OpenAI's internal projection (Reuters). The Q4 seasonal lift, the self-serve channel launch in May 2026, and international expansion push the exit run rate above the calendar-year average. Probability: 55%.
What this aggregates to: I would not buy OpenAI at IPO at $1 trillion. I would consider it at $700 billion if the step-change story stays on the table. I would short it at $1.3 trillion in the first week post-listing on the bet that institutional models catch up to the $25 billion loss number.
In the companion Anthropic forecast, I say I'd buy Anthropic at $965B if I could. Both views are consistent. Anthropic is a Mythos-equipped technical leader trading like a generic AI infrastructure bet. OpenAI is a consumer-and-ads incumbent trading like a winner-take-all software monopoly. The mispricing runs in opposite directions.
Run this forecast yourself by connecting FutureSearch to Claude and asking it to refresh the numbers any time the news cycle moves.