TAM

$300 billion

Definition: service-dollar TAM = annual global legal-fee revenue that could in principle be addressed by AI-powered 'associates' (document review, contract analysis, legal research, drafting, e-discovery and other high-volume, repeatable matter work). Methodology and calculation: 1) Start with a current global legal services market estimate (Precedence Research reports ~USD 0.99 trillion in 2024). 2) Evidence from industry studies shows that a large share of legal workflows are document- and research‑heavy (Thomson Reuters GenAI findings show document review, legal research and summarization among top GenAI use cases; independent whitepapers estimate roughly 35–38% of firm tasks are repetitive/amenable to automation). 3) To avoid overstating addressability, apply a conservative mid-point 'addressable share' of 30% of total legal-fee spend (reflects exclusion of litigated advocacy, bespoke strategic counseling and other tasks unlikely to be automated). Calculation: USD 0.99 trillion * 30% = USD 297 billion, rounded to USD 300 billion to express order-of-magnitude TAM. Key caveats: this number represents service-value potentially addressable by AI associates (annual legal fees), not the software/SaaS spend that vendors would capture directly (software spend will be a much smaller fraction of this service-value TAM). Actual realizable revenue will be lower and depends on pricing model (per-seat, per-matter, subscription), adoption curves, regulation, and competition.

• precedenceresearch.com
• legal.thomsonreuters.com
• scribd.com
• mckinsey.com
• reuters.com

SAM

$43.8 billion

Definition: U.S. law-firm service-dollar SAM = portion of the TAM that is realistically addressable by law-firm purchases in the United States in the near-to-medium term. Methodology and calculation: 1) Start with an estimate of the U.S. legal services market (Precedence Research and other market reports give a U.S. market in the low-to-mid hundreds of billions; Precedence Research lists roughly USD 292.1 billion for the U.S. in 2024). 2) Apply the same task-addressability factor used for TAM (30%) to isolate the share of U.S. legal fees tied to document/research/drafting work: USD 292.1B * 30% = USD 87.6B. 3) Constrain this to purchaser-available spend for law-firm buys (exclude in-house legal budgets, some ALSP-managed work, and work that is unlikely to be bought as a firm-wide AI-associate product). Applying a market-availability / near-term adoption factor of ~50% (reflecting adoption concentration in larger firms, smaller firms' limited tech budgets, and ALSP competition) yields SAM = USD 87.6B * 50% = USD 43.8B. Rationale: Thomson Reuters and Clio surveys document fast GenAI uptake but concentrated at larger firms; ABA tech reporting shows many solos/small firms have limited technology budgets; ALSPs are capturing part of routine/volume work. Alternative SAM definitions (for example, 'legal-AI software spend') are materially smaller today (single-digit billions) but are growing rapidly.

• precedenceresearch.com
• clio.com
• thomsonreuters.com
• statista.com
• reuters.com

SOM

$150 million

Definition: SOM = realistic revenue that an early-stage AI-associate vendor could capture from U.S. law firms within a 3–5 year commercial rollout (focused GTM on mid-market and large firms). Bottom-up scenario (illustrative, conservative-growth plan): 1) Addressable target pool: use total U.S. law-firm counts and industry distribution (Statista/industry reports indicate roughly 400k+ U.S. law-firm establishments; the initial commercial focus is on the subset of mid-size and large firms with budgets and procurement capacity — assume a targetable pool on the order of ~50,000 firms). 2) Penetration assumption: acquire 1,500 paying firms within 3–5 years (~3% penetration of that focused pool). 3) Pricing assumption: average annual contract value (ACV) of USD 100,000 per firm for a firm-wide AI-associate deployment (enterprise deployment or multi-matter subscription plus usage-based fees). Calculation: 1,500 customers * USD 100,000 ACV = USD 150,000,000 ARR. Alternative scenarios: conservative (750 customers * USD 100k = USD 75M), aggressive (3,000 customers * USD 100k = USD 300M). Rationale and evidence: the chosen ACV is consistent with enterprise legal-software pricing and with law-firm revenue-per-lawyer/technology budget benchmarks reported by industry sources; adoption rates and budgeting data (ABA, Clio, ILTA) show that larger firms both lead adoption and have the budgets to support six-figure enterprise deals. Key caveats: SOM excludes corporate in-house legal budgets and international expansion; actual SOM depends on conversion rates, retention, pricing mix (per-seat vs per-matter), and competitive dynamics.

• statista.com
• americanbar.org
• bestlawfirms.com
• clio.com
• emergenresearch.com