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AI PREMIUM · 2026

Why the AI premium poisons non-AI comp sets.

In 2026, AI-labelled startups raise at materially higher valuations than non-AI peers at the same stage. At seed the premium is around +46% (Carta 2025: AI seed median $19M pre-money vs $13M non-AI) and at Series A around +38%; it then escalates sharply at later stages, reaching roughly +193% by Series E+. For founders building non-AI companies, this matters operationally: if you include AI deals in your comparable benchmark set, you produce inflated valuation anchors that VCs reject in negotiation.

The premium by stage

Pre-seed
+40% AI premium over non-AI median
Seed
+46% AI premium over non-AI median
Series A
+38% AI premium over non-AI median
Series B
+60% AI premium over non-AI median
Series C+
+95% AI premium over non-AI median

Seed (+46%) and Series A (+38%) are taken directly from Carta 2025. Pre-seed, Series B and Series C+ are directional estimates following Carta's finding that the premium escalates at later stages (reaching ~193% at Series E+).

What this looks like in dollars

The blended Series A pre-money median is $48M, which already mixes AI and non-AI deals. Splitting it: non-AI median pre-money is roughly $42M and AI roughly $58M ($42M × 1.38). A founder pulling 10 Series A comps from Crunchbase or PitchBook in 2026 will get a mix — say 4 AI deals at $55-$80M and 6 non-AI at $38-$50M. The naive median across all 10 lands near $50M. Using that as your benchmark when you're non-AI overstates your defensible valuation by ~20%. The distortion is far larger if you reach into later-stage comps, where the AI premium balloons.

How to filter AI from comp sets

  1. Read each comp's positioning. If the company describes itself as “AI-native”, “AI-powered”, “LLM-first”, or includes generative-AI as core product, it's an AI deal even if the underlying SaaS category isn't.
  2. Check the round announcement language. AI deals consistently lead with model-capability claims, evaluation benchmarks, or training infrastructure. Non-AI deals lead with ARR, growth rate, or customer metrics.
  3. For ambiguous deals (a SaaS company that added an AI feature), check whether the marketing positioning treats AI as the core product or a feature. Core-AI = AI premium; AI feature = non-AI premium.
  4. If your comp set ends up with 6 AI and 4 non-AI deals, separate them. Report “AI median: $X. Non-AI median: $Y.” Then state which group you're benchmarking against.

If you ARE AI-native

The ~38% Series A premium is a blended average and is far from uniformly distributed. Foundation-model companies (OpenAI, Anthropic, Mistral peers) command the highest multiples — Series A foundational-AI medians can run several times the non-AI median. Application-layer AI (vertical SaaS with AI features) commands much smaller premiums, often only modestly above non-AI peers. AI infrastructure (training, inference, evaluation) sits in between. Pull comp sets from your specific AI tier, not the aggregate.

Practical recommendation:When VCs ask for your benchmark, lead with the AI/non-AI split. “Our 8 comps split 3 AI ($55M-$90M) and 5 non-AI ($38M-$50M). We're non-AI, benchmarking to the non-AI subset at ~$42M median.” This pre-empts the VC's likely objection about AI deals being in your set.