pre$premoneyvaluation.com
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. The premium peaks at Series A — AI deals price +85% over non-AI — and stays meaningful through Series C. 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
+25% AI premium over non-AI median
Seed
+35% AI premium over non-AI median
Series A
+85% AI premium over non-AI median
Series B
+70% AI premium over non-AI median
Series C+
+55% AI premium over non-AI median

What this looks like in dollars

Series A non-AI median pre-money: $48M. AI Series A median pre-money: ~$89M ($48M × 1.85). A founder pulling 10 Series A comps from Crunchbase or PitchBook in 2026 will get a mix — say 4 AI deals at $80-$120M and 6 non-AI at $40-$55M. The naive median across all 10 is approximately $65M. Using that as your benchmark when you're non-AI overstates your defensible valuation by 30%+.

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 +85% premium is the headline but it's not uniformly distributed. Foundation-model companies (OpenAI, Anthropic, Mistral peers) command the highest multiples. Application-layer AI (vertical SaaS with AI features) commands lower premiums — closer to +30-50% at Series A. 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 ($65M-$110M) and 5 non-AI ($35M-$58M). We're non-AI, benchmarking to the non-AI subset at $46M median.” This pre-empts the VC's likely objection about AI deals being in your set.