The 171% average ROI on enterprise agentic-AI deployments is the mean of a bimodal distribution — roughly 12% of deployments clear 300%+ and 88% sit at or below break-even. The single factor distinguishing the clusters is not a multi-pattern framework; it is whether business-line (not IT) ownership held the kill-switch and accountability before the deployment shipped.
Note hygiene 10 Jun 2026 (claim already Not holding since 28 Apr 2026): the bimodal 12/88 segmentation this claim attributed to the Stanford DEL 2026 playbook failed primary-source verification — the playbook studies 51 successful deployments and contains no ROI distribution (see AM-029 correction, 10 Jun 2026). Verified anchors that remain on the record: OneReach 171% average + Futurum 71% median productivity vs 40% high-automation, Gartner 28%-pay-off finding. The claim text retains its original wording as the immutable historical record. No further reviews scheduled.
Correction log
- 19 Apr 2026Body rewritten from WP-era slop (7-patterns vendor framework with fabricated case studies). New thesis: bimodal distribution, not normal — the 171% average describes no specific deployment. Business-line kill-switch ownership is the single distinguishing factor. Cross-links to AM-020 + AM-021 on the shared organisational-precondition thread.
- 28 Apr 2026Article retracted 28 Apr 2026. Slug carries '171% ROI' as a category average and a '7 proven patterns' framework that the body had to disown — the rewritten body explicitly argues 171% is the mean of a bimodal distribution, not a benchmark. Body rewritten 19 Apr 2026 (preserved in archived/) but the slug contradicts the rewritten thesis and Google has rejected the URL. URL now redirects to /retractions/?retired=the-agentic-ai-success-formula-7-proven-patterns-driving-171-roi-in-enterprise-deployments. Claim withdrawn — status moves to Not holding, no further reviews scheduled.
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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-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.
- AM-201 · Partial · 10 Jun 2026
One of four named datasets unanchored on review. The claim text names 'Stanford DEL's 12% clearing 300%+ ROI vs 88% at or below break-even' as one of four independent datasets. Full-text verification on 10 Jun 2026 found the Stanford DEL Enterprise AI Playbook contains no such distribution — it studies 51 successful deployments by design and carries no ROI-realisation failure data (full finding at AM-029, correction of 10 Jun 2026). The McKinsey (23% scaling, 17% EBIT-attribution), Gartner (28% fully paying off), and MIT NANDA (95% no measurable P&L impact) datasets verify; the claim's spine stands on three datasets rather than four. 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 from an ROI distribution. Status Up -> Partial.
Reviews coming up in Reporting
- AM-063 · Holding · next +15d (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 +15d (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 +15d (27 Jun 2026)
GPT-5 Pro's tiered-subscription model forces enterprises to classify problems by computational difficulty — $200/month…