The 2026 enterprise agentic AI orchestration-framework choice across the five major frameworks (AWS Bedrock AgentCore GA October 2025, Microsoft Azure AI Foundry plus Copilot Studio, Google Vertex AI Agent Builder plus the open-source Agent Development Kit, OpenAI Agent Builder GA October 2025 plus the open-source Swarm primitive, Anthropic Claude Agent SDK late 2024 plus the open-source Model Context Protocol) prices the decision as a 3-year orchestration-layer commitment along five comparison axes (orchestration primitive, tool-use protocol, deployment topology, observability tier, exit cost), with the framework choice resolved by gravity-fit against the customer's existing cloud, identity, and data substrate rather than by model-tier performance; the 2026 cross-vendor convergence on the Model Context Protocol as the tool-use standard is the structural change that makes exit cost newly tractable for customers who write tool definitions in the protocol and emit OpenTelemetry traces, materially lowering the year-three re-platforming cost relative to the framework-native alternatives.
Anchored on (a) AWS Bedrock AgentCore product documentation (GA October 2025 with Runtime, Memory, Identity, Gateway, Code Interpreter, Browser, Observability primitives); (b) Microsoft Azure AI Foundry product documentation (late 2024 rebrand from Azure AI Studio; Copilot Studio multi-agent orchestration 2025 expansion; November 2024 autonomous agents launch; 2025 Microsoft Agent 365 management surface); (c) Google Vertex AI Agent Builder + ADK (open-sourced 2024) + Agents Garden managed catalogue; (d) OpenAI Agent Builder GA October 2025 + Assistants API persistence layer + open-source Swarm primitive; (e) Anthropic Claude Agent SDK late 2024 + Model Context Protocol November 2024 launch (modelcontextprotocol.io) + 2025 cross-vendor adoption. The competitive-position characterisation is from current vendor documentation; future framework reframes (a Foundry-to-something-else rename, an AgentCore architecture pivot, the Vertex AI roadmap acceleration) would change the matrix. 60-day review cadence (26 Jul 2026). Trigger conditions: (1) major vendor announcing structural framework reframe moves toward Partial; (2) Model Context Protocol or alternative tool-use standard achieving genuine cross-vendor portability (not just adoption) changes exit-cost axis materially; (3) published independent (non-vendor-funded) benchmark comparing the five frameworks on enterprise deployment outcomes (latency, cost, error rates at production scope) hardens or weakens competitive position claims; (4) major partnership shifts (Microsoft-OpenAI restructure, AWS-Anthropic deepening, Google first-party competitiveness narrowing) reshape comparison. Sibling pairwise /compare/ pages cover model-tier comparisons (orchestration layer constant, model variable); AM-169 covers the protocol-tax piece (MCP vs A2A vs Llama Stack) at the protocol-level decision.
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The claim: The 2026 enterprise agentic AI orchestration-framework choice across the five major frameworks (AWS Bedrock AgentCore GA October 2025, Microsoft Azure AI Foundry plus Copilot Studio, Google Vertex AI Agent Builder plus the open-source Agent Development Kit, OpenAI Agent Builder GA October 2025 plus the open-source Swarm primitive, Anthropic Claude Agent SDK late 2024 plus the open-source Model Context Protocol) prices the decision as a 3-year orchestration-layer commitment along five comparison axes (orchestration primitive, tool-use protocol, deployment topology, observability tier, exit cost), with the framework choice resolved by gravity-fit against the customer's existing cloud, identity, and data substrate rather than by model-tier performance; the 2026 cross-vendor convergence on the Model Context Protocol as the tool-use standard is the structural change that makes exit cost newly tractable for customers who write tool definitions in the protocol and emit OpenTelemetry traces, materially lowering the year-three re-platforming cost relative to the framework-native alternatives.
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…