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There is no single “AI startup multiple” that tells you what a company is worth in a downturn. Investors weigh the company’s stage, revenue and growth evidence, comparable deals, cash needs, runway and financing terms. A previous round can inform that judgment, but may no longer reflect current conditions; meanwhile, strong demand for some AI companies can coexist with discounts and tighter funding elsewhere in venture capital.
Why a previous round may not be today’s value
A negotiated financing price is evidence of what investors and a company agreed at a particular time, under particular conditions. It is not a continuously updated market quote. When fundraising slows and rounds become less frequent, the last price can grow stale even if it remains the reference used for a portfolio mark.
Commonfund’s 2023 analysis describes venture managers updating private-company marks quarterly and often using the last private financing price. It also reports an average 23% discount to last-round price across the venture-manager holding marks in its sample. That figure describes those studied marks—not a standard discount for every startup, a current offer to founders, or the price of a new financing.
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Infrequent transactions also make it difficult to know what a company could raise for now. A portfolio mark, a new round’s negotiated price and the amount an investor might realize in a sale are different measures; they need not match.
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How investors and fund managers estimate value
Use the last financing as a reference point
When a company has raised recently, its latest financing can provide a concrete reference. In a slower market, investors scrutinize how long ago that transaction happened and whether the company, its prospects or the financing environment have changed since. A historical round price is an input, not proof that the same price is available today.
Compare with public companies
When there is no fresh private financing, managers may apply valuation multiples from public companies to the startup’s operating measures. The result depends on which companies are considered comparable and which measures—such as revenue—are used. A company’s AI label alone does not establish that a particular public-company multiple applies.
Account for different rights in the capital structure
Where shares or other securities have different rights, an option pricing model can help allocate value among them. Commonfund describes these models as using statistical inputs such as the risk-free rate, volatility and equity risk premium. This is one reason a company’s overall headline valuation does not by itself reveal the value of every security.
Update estimates with market and company indicators
PitchBook describes its Valuation Estimates product as updating last-known valuations using public and private comparables and company-specific indicators, including employee growth and company age. This is PitchBook’s description of its own product, not independent validation of the estimates or a universal valuation method. PitchBook also says private-company pricing can vary with who is transacting and why, particularly when liquidity is uneven.
What investors examine in a new AI financing
For a new investment, investors assess the company’s evidence and the financing it needs, rather than simply applying a sector-wide figure. Relevant considerations include:
- Stage and operating evidence: the company’s maturity, revenue, growth and other support for its business prospects.
- Comparable transactions: their date, stage, geography and deal type, as well as whether the comparison is genuinely relevant.
- Capital requirements: the cash needed for talent, chips, infrastructure and other costs, and how much time the proposed financing is intended to provide.
- Runway and alternatives: how long the company can operate with available cash and what financing options it has.
- Financing terms: the rights attached to the securities and other deal terms, not just the headline amount raised or post-money figure.
These factors interact. A company that needs substantial capital may seek a larger raise or negotiate a different structure to extend its runway. The amount invested and the post-money valuation alone do not show all of the economics or what investors may ultimately earn.
Why AI demand can hold up while venture funding tightens
AI financing has not moved in lockstep with the broader venture market. PitchBook describes premiums for selected AI startups alongside pressure on many other companies, including valuation discounts for firms without recent rounds. That is a market observation, not a guarantee that an AI company will command a premium.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteThe OECD’s analysis of global venture investment, using Preqin data and OECD keyword analysis, found that AI firms received USD 258.7 billion—61% of worldwide VC investment—in 2025. The same analysis found that deals over USD 100 million accounted for about 73% of AI VC investment value, while AI IT infrastructure and hosting received USD 109.3 billion. These figures describe aggregate investment activity, not typical company valuations or a funding outcome available to every AI startup. Deal classifications and records for smaller deals can be revised retroactively, and the OECD cautions that VC data show only one part of AI investment.
The concentration in large deals and infrastructure helps explain why a strong AI headline can coexist with difficulty raising for an individual business. Investors still need to assess the company’s specific prospects and capital requirements. The Q3 2025 PitchBook-NVCA report connects large AI funding needs with spending on talent, chips and infrastructure, as well as the pressure to deliver returns to investors.
What slower fundraising means for valuation benchmarks
Silicon Valley Bank’s H1 2025 report describes slower valuation growth, lower revenue multiples amid tighter capital supply and slower growth, and pressure on companies’ runway. Its benchmarks are based on SVB’s analysis with PitchBook and SVB data; they are not global or AI-specific valuation rules.
For context, SVB reported median annual revenue of USD 2.5 million for a Series A company, 75% higher than in 2021. It defines this as annualized current run rate and excludes extension rounds. SVB also reported that the typical Series A company takes more than two years to increase its valuation as much as companies in 2021 did in a single year. Neither comparison establishes what a particular AI startup should be worth.
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Before using a financing headline or market benchmark to estimate a company’s value, check what the number actually represents:
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- Identify stage and geography. A comparison is more informative when it refers to companies at a similar stage and in a relevant market.
- Check the date and deal type. A recent negotiated financing and an older portfolio mark are not interchangeable.
- Separate pre-money from post-money value. These describe the company’s value before or after the new investment, respectively; do not treat them as the same figure.
- Inspect the operating evidence. Compare revenue, growth and other relevant indicators rather than relying on an AI label or a sector average.
- Account for capital needs and runway. Compute, talent and infrastructure requirements can shape the size and structure of a financing.
- Read the terms as well as the headline. Security rights and other terms affect what a quoted valuation means to the company and its investors.
These checks help explain why two reported valuations—or a financing price and a later manager mark—can differ without one number being a universal answer.
Is there a standard AI startup valuation formula?
No universal AI-specific formula or revenue multiple is established by the available market evidence. Aggregate reports do not provide an apples-to-apples comparison separating foundation-model companies, AI applications, infrastructure providers and AI-enabled businesses across stages and geographies. A reported sector average is therefore context, not a valuation for an individual company.
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