The 2026 'compare AI agent vendors regulated enterprise' procurement question resolves to four sector-specific vendor matrices, not one universal scorecard; each begins with a structural disqualification pass on the regulatory baseline (FedRAMP High plus DoD Impact Level for federal-civilian and defence; HIPAA BAA plus FDA 21 CFR Part 11 plus HITRUST plus EU AI Act Article 6/14 for healthcare and pharma; Federal Reserve SR 11-7 plus NYDFS Part 500 plus FINRA RN 24-09 plus SEC Rule 17a-4 for US financial services; NERC CIP plus EU NIS2 plus ISA/IEC 62443 plus regional reliability operator data-handling for energy and utility), populates a 5-or-6-row matrix per vertical against the surviving vendors, and translates the row gaps into contractually enforceable MSA addenda (the AM-167 NHI procurement-clause work instruments); the energy and utility matrix is structurally thinner than the other three because the OT/ICS overlay disqualifies most general-purpose agentic AI platforms in favour of the OT-specialist tier (Claroty, Dragos, Nozomi) with AI overlays.
Anchored on (a) FedRAMP Marketplace listings for cloud service offerings (Microsoft Azure Government Community Cloud High, AWS GovCloud, Google Cloud Assured Workloads, Salesforce Government Cloud Plus) plus the DoD Cloud Computing Security Requirements Guide Impact Levels (IL2 through IL6); (b) HHS HIPAA Privacy and Security Rules, FDA 21 CFR Part 11 (electronic records and signatures), HITRUST CSF certification framework, EU AI Act Articles 6 (high-risk classification) and 14 (human oversight), GDPR Article 9 (special-category data); (c) Federal Reserve SR 11-7 model risk management guidance, 23 NYCRR Part 500 (NYDFS cybersecurity) and the 2023 third-party amendments, FINRA Regulatory Notice 24-09 (AI in customer communications, 2024), SEC Rule 17a-4 (records retention); (d) NERC CIP standards 002-014 (with CIP-013 supply chain risk most relevant), EU NIS2 Directive 17 Oct 2024 implementation deadline, ISA/IEC 62443 industrial cybersecurity standards. The vendor-product current-state characterisation is from May 2026 vendor documentation; future certification advancements (additional FedRAMP High regions, NERC CIP cloud-services advancement, HITRUST inheritance scope expansion) would change the matrix specifics. 60-day review cadence (26 Jul 2026). Trigger conditions: (1) major agentic AI platforms announcing new sector-specific certification tiers that materially shift the disqualification pass move toward Partial; (2) a published regulatory enforcement action against an agentic AI deployment in any of the four verticals provides concrete precedent and reshapes regulatory-fine pass-through framing; (3) EU AI Act implementing acts shipping mandatory technical standards under Articles 6/14/15 warrants a regulated-vertical-by-vertical update; (4) NIST releasing AI RMF 2.0 or sector-specific profiles (healthcare and financial-services profiles anticipated) expands the federal and adjacent-sector matrices. Sibling AM-172 covers US-frameworks treatment; AM-167 covers MSA-layer procurement clause instruments; EU AI Act corpus at /topic/agentic-ai-governance/ covers the cross-vertical baseline.
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The claim: The 2026 'compare AI agent vendors regulated enterprise' procurement question resolves to four sector-specific vendor matrices, not one universal scorecard; each begins with a structural disqualification pass on the regulatory baseline (FedRAMP High plus DoD Impact Level for federal-civilian and defence; HIPAA BAA plus FDA 21 CFR Part 11 plus HITRUST plus EU AI Act Article 6/14 for healthcare and pharma; Federal Reserve SR 11-7 plus NYDFS Part 500 plus FINRA RN 24-09 plus SEC Rule 17a-4 for US financial services; NERC CIP plus EU NIS2 plus ISA/IEC 62443 plus regional reliability operator data-handling for energy and utility), populates a 5-or-6-row matrix per vertical against the surviving vendors, and translates the row gaps into contractually enforceable MSA addenda (the AM-167 NHI procurement-clause work instruments); the energy and utility matrix is structurally thinner than the other three because the OT/ICS overlay disqualifies most general-purpose agentic AI platforms in favour of the OT-specialist tier (Claroty, Dragos, Nozomi) with AI overlays.
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…