The 2026 enterprise agentic AI procurement playbook resolves to a six-stage sequence that integrates the build-vs-buy-vs-partner decision, the 60-question agentic AI RFP, the GAUGE governance scoring, the four-vendor comparison, and the EU AI Act compliance scaffolding into one operational track. Most enterprises in 2026 run these as separate work streams owned by separate functions, which produces structurally inconsistent procurement records and substantial duplicate effort. The integrated six-stage track ships in 8 to 10 weeks for standard environments and produces an audit-defensible per-deployment procurement artifact that satisfies the EU AI Act Article 9 risk-management system requirement by construction.
Re-review 10 Jun 2026: holds. EU AI Act Article 9 anchor verified verbatim against artificialintelligenceact.eu ('A risk management system shall be established, implemented, documented and maintained in relation to high-risk AI systems', continuous iterative process across the lifecycle) — the by-construction satisfaction argument stands. Two constituent-framework events logged, both below the major-change bar of watch 1: GAUGE changelog v1.0.2 (10 Jun 2026) withdrew the calibration citation with dimensions and weights unchanged, and AM-039 (the four-vendor comparison) went Partial the same day on its BAA-attribution sentence — Stage 2 regulatory rule-out guidance inherits the hyperscaler-BAA nuance but the six-stage sequence and its outputs are unaffected. Procurement playbook claim is scoped to enterprise agentic AI procurement specifically. The six-stage sequence is portable to adjacent procurement categories (data platforms, observability stacks) but is not optimised for them. 60-day review cadence. Watches: (1) major changes to any of the four constituent frameworks (build-vs-buy criteria, the 60-question RFP, GAUGE dimensions, vendor landscape), (2) regulatory enforcement that materially changes the documentation bar at any stage, (3) procurement-platform vendors that ship native integration of any combination of the constituent frameworks (would compress engineering work substantially).
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The claim: The 2026 enterprise agentic AI procurement playbook resolves to a six-stage sequence that integrates the build-vs-buy-vs-partner decision, the 60-question agentic AI RFP, the GAUGE governance scoring, the four-vendor comparison, and the EU AI Act compliance scaffolding into one operational track. Most enterprises in 2026 run these as separate work streams owned by separate functions, which produces structurally inconsistent procurement records and substantial duplicate effort. The integrated six-stage track ships in 8 to 10 weeks for standard environments and produces an audit-defensible per-deployment procurement artifact that satisfies the EU AI Act Article 9 risk-management system requirement by construction.
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…