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AI Company Valuation (2026)

AI software companies trade across a very wide band — roughly 8–45× revenue in 2026 — because valuation hinges on defensibility, not just growth. A thin wrapper on a foundation model and a company with proprietary data and owned IP sit at opposite ends.

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AI revenue multiples by defensibility (2026)

ProfileVerdictRevenue multiple
Wrapper (no IP, high model dependence)Wrapper risk~8–14×
Mixed (some product + data)Mixed~14–25×
Defensible IP + proprietary dataDefensible~28–45×

Ranges from real 2026 lower-middle-market transaction data. Sources: aventis-advisors.com/saas-valuation-multiples, ctacquisitions.com/ebitda-multiple-by-industry-2026, equidam.com/ebitda-multiples-trbc-industries, praxisrock.com/insights/ebitda-multiples-by-industry, l40.com/insights/saas-multiples. Your specific multiple depends on the value drivers below.

What determines an AI company's multiple

Defensibility is scored on: owned model/IP, a proprietary data moat, share of revenue that's true product vs. services, gross margin (inference-cost durability), and foundation-model dependence (inverse). Low defensibility = wrapper risk and a single-digit multiple; strong defensibility earns the 40–50× tier.

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FAQ

What revenue multiple do AI companies get in 2026?

AI software spans 8–45× revenue depending on defensibility. Wrappers on foundation models sit at the low end; companies with owned IP and proprietary data reach the top.

Why do some AI startups get 40× revenue and others 5×?

Defensibility. Owned models, proprietary training data, high product (not services) revenue, strong margins, and low foundation-model dependence justify premium multiples. Thin wrappers do not.

Is my AI company a wrapper or defensible IP?

If most value comes from prompting a third-party model with no proprietary data or owned IP, buyers treat it as a wrapper. Proprietary data and owned models move you into defensible territory.

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