Agentic AI 2024-2025 produced four distinct classes of evidence the 2026 procurement reader should not collapse into a single 'AI is working' narrative: (1) vendor-published wins inside vendor-controlled environments (ServiceNow internal 90% L1 deflection, framed by Nenshad Bardoliwalla as upper bound conditioned on two decades of structured workflow data the customer does not have), (2) audited customer pilots with active human oversight (BT 35% case-resolution improvement with random checks per Hena Jalil; UK Government Digital Service 26 minutes/day saved across 20,000 staff in Q4 2024; HMRC 28,000-staff M365 Copilot rollout April 2026), (3) public walk-backs (Klarna May 2025 Bloomberg-reported reversal of the 700-agent claim while the original press release stayed live; GitHub Copilot April 2026 token-counting bug; Salesforce Agentforce IT 200-customer reality vs Marc Benioff's launch pitch), and (4) structural failure modes (CRMArena-Pro 35% multi-step agent reliability finding; Carnegie Mellon independent verification at 30-35%; EchoLeak CVE-2025-32711 cross-agent prompt-injection class). Each class produces a different procurement lesson; treating them as one narrative is the most common 2026 enterprise mistake.

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.

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.

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.

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