Across the 2025–2026 documented deployments at AmLaw 100 firms, agentic AI captures durable value in three of the six billable-hour sub-tasks (document review, precedent retrieval, deposition prep) and produces a net malpractice-risk increase in two (legal drafting submitted as final, citation generation) vs a junior-associate-drafted equivalent at the same time-to-delivery; the remaining sub-task (client communication) is bounded by professional-conduct rules, not technology.
Claim created at publish. Three-value sub-tasks grounded in Allen & Overy / Harvey deployment outcomes (FT, Law.com coverage) and Lexis+ AI / Westlaw Precision vendor disclosures. Two-risk sub-tasks grounded in Mata v. Avianca (S.D.N.Y. Jun 2023) and Park v. Kim (2nd Cir. Jan 2024) sanctions, plus Stanford CodeX hallucination-rate data on legal-specific LLMs. The critical comparator in the claim is vs junior-associate-drafted equivalent at the same time-to-delivery, not vs zero; the claim overstates if read without that comparator. Client-communication bound grounded in ABA Formal Opinion 512 (Jul 2024) and Model Rule 1.4. Malpractice insurance angle: e&o carrier tightening on AI-final-drafted work cited as directional; the synthesis is labelled source:our-estimate in the article body. 90-day review cadence. Trigger conditions: (a) e&o carrier publicly underwriting AI-final-drafted filings — collapses the two-risk sub-task finding for that task class; (b) second sanction wave in 2026 H2 — reinforces or extends it; (c) ABA / EU bar guidance shift post-FO 512 that expressly relaxes or tightens the client-communication bound; (d) Stanford CodeX or comparable independent hallucination-rate re-run on a legal-specific LLM showing sustained <5% hallucination on citation-generation tasks.
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The claim: Across the 2025–2026 documented deployments at AmLaw 100 firms, agentic AI captures durable value in three of the six billable-hour sub-tasks (document review, precedent retrieval, deposition prep) and produces a net malpractice-risk increase in two (legal drafting submitted as final, citation generation) vs a junior-associate-drafted equivalent at the same time-to-delivery; the remaining sub-task (client communication) is bounded by professional-conduct rules, not technology.
About this register
The Reporting register tracks claims published from articles addressed to senior enterprise IT leaders — CIOs, IT directors, heads of platform. Claims are reviewed on a 30–90 day cadence; each review either reaffirms the claim, marks one substantive part as Partial, or marks it Not holding once the underlying evidence has been overtaken.
Recent corrections in Reporting
- AM-008 · Partial · 17 Jun 2026
Source-text figure re-review: Google's 2024 Environmental Report reports a 28% year-over-year increase to 8.1 billion gallons, not the 33% (from a 6.1 billion 2023 base) asserted at publish. The 8.1B 2024 figure and the Microsoft WUE 0.30 L/kWh / 39%-improvement figure are unchanged and verified. Article corrected to 28% and the unsupported 6.1B base removed; the claim text retains the original figure with this correction per the Holding-up protocol.
- AM-132 · Partial · 10 Jun 2026
One of four legs unanchored on re-review. The claim text attributes '12% of deployments clearing 300%+ ROI with 88% at or below break-even at 12-18 months' to the Stanford DEL 2026 Enterprise AI Playbook. Full-text verification on 10 Jun 2026 found no such figure in that source: the playbook (Pereira, Graylin, Brynjolfsson, Apr 2026) studies 51 successful deployments by design and contains no ROI distribution, no 300%-plus cohort, and no break-even measurement point (full finding at AM-029, correction of 10 Jun 2026). The only verified figure carrying the same 12/88 numerals is IDC research with Lenovo (via CIO.com, Mar 2025): roughly 88% of AI proof-of-concepts never reach production and roughly 12% graduate — a pilot-to-production graduation metric, not an ROI distribution. The Gartner 28%, McKinsey 23%/17%, and MIT NANDA 95% legs verify; they support a small high-performing tail and a large struggling body, but none documents the two-peak bimodal shape the claim asserts. Status Up -> Partial.
- AM-129 · Partial · 10 Jun 2026
One of three read-against anchors unanchored on re-review. The claim text cites 'Stanford Digital Economy Lab Enterprise AI Playbook (12/88 bimodal ROI distribution at 12-18 months)' and frames the realistic ROI band around 'the highest-discipline 12% cohort'. Full-text verification on 10 Jun 2026 found the playbook contains no 12/88 distribution, no bimodal ROI shape, and no 12-18-month ROI measurement point (full finding at AM-029, correction of 10 Jun 2026). The claim's core negative finding — no mid-market enterprise has produced a documented +240% ROI in 90 days under audited conditions — is unaffected; the McKinsey State of AI 2025 and MIT NANDA legs verify and continue to support it. The '12% cohort' framing has no verifiable referent. The only verified figure carrying the 12/88 numerals is IDC's pilot-graduation finding (roughly 88% of AI proof-of-concepts never reach production; via CIO.com, Mar 2025), a different metric. Status Up -> Partial.
Reviews coming up in Reporting
- AM-063 · Holding · next +9d (27 Jun 2026)
AI agents executing financial transactions need a four-control bundle (action-approval gates by blast radius, kill-swit…
- AM-061 · Holding · next +9d (27 Jun 2026)
Production agentic-AI costs at scale routinely run multiples of POC projections, and a layered optimisation programme c…
- AM-003 · Partial · next +9d (27 Jun 2026)
GPT-5 Pro's tiered-subscription model forces enterprises to classify problems by computational difficulty — $200/month…