Directions Brain

vertical-ai-tam

3 min read

Vertical AI TAM

Definition

The market-sizing framing that the right denominator for vertical AI is labor spend, not software spend — because vertical AI products replace human work, not just other software. Cited in 2026-05-01-entree-capital-enterprise-ai-spend-map from Scale Venture Partners and NEA: vertical AI targets ~450B US SaaS market, a ~25x larger pool. This is the load-bearing TAM argument for vertical-use-case-led-brain when pitching to investors.

Key points

  • The 25x denominator. Traditional SaaS sizing asks “what % of US software budget?”; vertical AI sizing asks “what % of US labor cost in this function?“. The latter is one to two orders of magnitude larger.
  • Bessemer’s portfolio data point. Bessemer reports its vertical-AI portfolio grew +400% YoY at ~65% gross margin (2026-05-01-entree-capital-enterprise-ai-spend-map citing Bessemer’s “The future of AI is vertical”, Aug 2025). 65% GM at this growth rate is unusual — suggests vertical AI is not a margin-compressed reseller of frontier APIs, despite the token-cost flow described in the same source.
  • The 2026–27 vertical breakouts named in the report: legal (Harvey is the canonical example), healthcare, financial services. First vertical AI IPOs expected 2027–28 (Bessemer).
  • The pitch math for the team. A vertical wedge in healthcare (e.g. ari-leshno’s clinical-data-portability glaucoma play) sits inside this 450B one. The ceiling argument from vertical-use-case-led-brain (“nobody pays $1M ARR for a wiki”) inverts: clinics replacing technician hours / specialist scarcity will pay multiples of the SaaS comparison if the workflow ROI lands.
  • Caveat: “labor TAM” is a sales narrative, not addressable TAM. Most labor cost is not literally substitutable by AI in 2026; the realistic capture is single-digit percent in the medium term. The 25x framing is a pitch ceiling, not a forecast.

Evidence

Open questions

  • What fraction of the $11T US labor pool is realistically AI-substitutable by 2030 vs 2040? The report doesn’t quantify; needs independent triangulation before the team uses this number in a pitch.
  • Does the +400% YoY at 65% GM hold for early-stage Bessemer portfolio (small denominators) or has it persisted at scale? Needs deeper Bessemer / public-comp validation.
  • Which sub-verticals inside the $11T have the highest AI-substitution coefficient — i.e. where the labor → software flip is fastest? Legal (Harvey) is one anchor; healthcare and financial services are next. Within healthcare, where in particular?
  • Does the team’s chosen vertical (TBD) sit on the right side of the substitution curve, or is it labor-heavy in ways AI doesn’t touch yet?

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