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Holding·last review14 Jun 2026

The EU AI Act's enforcement calendar splits in two: general-purpose AI model-provider obligations become directly enforceable on 2 Aug 2026 (finable up to 3% of global annual turnover or €15M), while the provisionally agreed Digital Omnibus defers high-risk deployer obligations for stand-alone Annex III systems to 2 Dec 2027, so enterprises face their AI vendors' new compliance demands roughly 16 months before their own high-risk deadline arrives.

Drafted 14 Jun 2026, awaiting Peter's publish-move. Fresh angle distinct from prior regulation pieces (AM-184 Omnibus reality-check, AM-186 delay-readiness, AM-197 federal-state standoff, AM-207 White House EO). Verified: GPAI model-provider supervision/enforcement powers take effect 2 Aug 2026 (one-year grace from 2 Aug 2025 ends); GPAI penalty up to 3% of global turnover or €15M (Art 101); pre-2-Aug-2025 GPAI models have until 2 Aug 2027; Digital Omnibus on AI tabled 19 Nov 2025, provisional political agreement 7 May 2026, IMCO+LIBE committee approval 2 Jun 2026, final plenary vote still pending as of mid-Jun 2026 (so deferral is the likely outcome, not settled law); Omnibus defers stand-alone Annex III high-risk to 2 Dec 2027 and Annex I-embedded to 2 Aug 2028; Art 5 prohibited practices in force since 2 Feb 2025. PRECISION: the 3%/€15M figure is sourced via reference trackers (artificialintelligenceact.eu) reflecting Act Art 101; the procedural status via the europarl legislative-train. Expert quote: Anu Talus, Chair, EDPB (EDPB/EDPS joint opinion, 11 Feb 2026). Triggers: (1) the Digital Omnibus fails its final vote or changes the deferred dates; (2) the Commission moves the GPAI enforcement date; (3) the first AI Office enforcement action re-reads the practical posture. Siblings: AM-184, AM-186, AM-197.

Published
14 Jun 2026
Last reviewed
14 Jun 2026
Next review
+88d· 12 Sep 2026
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The claim: The EU AI Act's enforcement calendar splits in two: general-purpose AI model-provider obligations become directly enforceable on 2 Aug 2026 (finable up to 3% of global annual turnover or €15M), while the provisionally agreed Digital Omnibus defers high-risk deployer obligations for stand-alone Annex III systems to 2 Dec 2027, so enterprises face their AI vendors' new compliance demands roughly 16 months before their own high-risk deadline arrives.

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.

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