Executive Summary
Legal teams at telecommunications firms operating across international jurisdictions face a specific and consequential AI failure when consulting AI tools on the OECD's 2025 Merger Review Recommendation: the importation of a foreign regulatory framework's remedy hierarchy as though it were the Recommendation's operative text. Across the questions we put to AI assistants on this regulation, AI tools produced a hallucinated internal sub-tier ordering within Section IV.3's structural remedies, an ordering drawn from EU merger-control practice, that does not appear anywhere in the Recommendation itself.
The Recommendation's actual priority within structural remedies is a standalone-business-divestiture preference; AI tools replaced that with a timing-based three-step hierarchy (fix-it-first, upfront buyer pool, crown jewel) that is EU doctrine, not OECD doctrine. For a telecommunications firm navigating a cross-border merger review simultaneously under multiple regimes, a Legal team that trusts this AI answer faces the risk of building an internal remedies analysis, or advising deal teams, on a compliance framework that is jurisdictionally wrong for any proceeding conducted under the OECD's recommendations.
How AI gets this regulation wrong
The AI failure pattern on this regulation is misattribution: AI assistants cited a real source, or drew on genuine regulatory concepts, but attributed content to the OECD Recommendation that actually belongs to a different regime entirely. The result is not a made-up rule so much as a real rule transplanted from the wrong jurisdiction, which is harder to catch precisely because the underlying concept (remedy hierarchy in merger control) sounds plausible in context.
| AI's Failure Mode | Count | Affected findings |
|---|---|---|
| Misattributed | 1 | Finding#1 |
What that means for your team
When AI tools import the wrong regime's doctrine into a remedies analysis, the downstream risk for Legal is a wrong deliverable, an internal memo, board briefing, or deal-team guidance note that encodes a compliance framework the actual regulation does not support. For a telecommunications firm running concurrent merger reviews across multiple jurisdictions, a regime-contamination error in the foundational remedies analysis compounds: it propagates into every downstream artefact that references it before anyone catches the source confusion.
| Risk Impact | Count | Affected findings |
|---|---|---|
| Wrong deliverable | 1 | Finding#1 |
When this affects your department
The OECD Merger Review Recommendation becomes operationally live for a telecommunications firm's Legal function at the moment a proposed transaction enters the regulatory scoping phase, whether that is a spectrum acquisition, a national network infrastructure deal, or a cross-border consolidation involving OECD-member-state regulators. Legal will typically be asked to produce an internal remedies risk register, advise the deal team on the likely form and sequencing of remedy negotiations, and brief the board or transaction committee on the regulatory exposure ahead of signing.
AI tools are attractive at this stage precisely because the turnaround window is tight and the jurisdiction footprint is wide; a general-purpose AI assistant that can appear to synthesise OECD, EU, and national competition-authority frameworks in one response saves significant drafting time.
The specific failure here, the substitution of EU practice for OECD doctrine in Section IV.3's remedy ordering, surfaces most dangerously when Legal is producing the initial remedies analysis to frame internal strategy. If a junior associate or paralegal generates that analysis using an AI tool and the output presents a plausible-sounding three-tier structural remedy hierarchy (fix-it-first ranked first, upfront buyer pool second, crown-jewel packages third), a reviewer who is not already expert in the OECD Recommendation's precise text will not immediately recognise that the hierarchy is EU doctrine imported wholesale.
The OECD's actual priority, divestiture of standalone businesses within the structural tier, is directionally consistent with parts of EU practice, which makes the contamination even harder to detect on a cursory read.
If this error travels forward into the remedies analysis that the deal team takes to the transaction committee, the firm's internal strategy is calibrated against the wrong hierarchy. More concretely: if the firm pre-commits deal resources, carve-out preparation, trustee mandates, buyer outreach, according to an EU-style sequencing that the OECD Recommendation does not prescribe, and the relevant review authority is applying OECD guidance, the firm's negotiating posture may be misaligned with the authority's expectations from the opening of remedy discussions.
In a sector where spectrum licences, network-sharing agreements, and infrastructure divestitures are the structural remedy toolkit, calibrating that toolkit against the wrong framework is not a theoretical risk.
The findings at a glance
The table below shows each finding on the OECD Merger Review Recommendation (2025 Revision) where AI assistants produced a materially wrong answer when queried on provisions directly relevant to Legal teams at telecommunications firms in international jurisdictions.
| # | Finding title | Type | Citation ID |
|---|---|---|---|
| 1 | Section IV.3 structural remedy priority, EU doctrine imported as OECD text | Hallucination | RLB-F-INT-OECD-OECD-MERGER-REVIEW-RECOMMENDATION-2025-Q002 |
Aggregate impact
The single finding on this regulation is structurally telling: the AI error is not a fabrication out of whole cloth but a regime-contamination, an authoritative-sounding hierarchy that is real in one jurisdiction presented as if it were the operative text of a different instrument. For a Legal function that routinely works across EU, national, and OECD-framework merger reviews simultaneously, this is precisely the failure mode that professional reviewers are least likely to catch, because the contaminating content (EU structural remedy sequencing) is part of the team's working knowledge. The error is invisible unless the reviewer checks Section IV.3 verbatim.
The finding clusters on the core operational provision for Legal: how to rank and sequence remedies when advising on a transaction that triggers review. That is not a peripheral interpretive question, it is the provision that drives internal strategy from day one of the regulatory engagement. A wrong answer here does not merely produce a faulty memo; it shapes the trajectory of board-level decisions, the structure of carve-out preparations, and the firm's opening position in remedy negotiations with competition authorities across member states.
For telecommunications firms operating internationally, the systemic risk is amplified by the multi-jurisdictional character of the sector's deal activity. Spectrum acquisitions, tower-sharing deals, and national-champion consolidations often trigger simultaneous review by OECD-member-state authorities and the European Commission. When Legal is mapping the remedies landscape across those parallel proceedings, a regime-contamination error in the OECD analysis does not stay siloed, it infects the comparative framework that the team uses to identify where OECD and EU obligations align and where they diverge. The firm ends up with a spurious alignment that obscures real differences.
What your team should do
The default position for Legal on this regulation is straightforward: do not use AI tools to generate the operative text of specific provisions, and do not allow AI-generated remedies analyses to travel forward as the foundational document for deal-team strategy without a verbatim check against the Recommendation itself. The specific failure here, EU doctrine presented as OECD Section IV.3 text, would have been caught immediately if the reviewer had opened the Recommendation and read IV.3 alongside the AI output. That check takes two minutes and belongs in the workflow as a hard gate, not an optional quality step.
Practically, the safeguard is to treat AI tools as useful for horizon-scanning and comparative framing, identifying which sections of the Recommendation are likely to engage for a given deal profile, flagging which member-state implementing frameworks differ from the OECD baseline, synthesising commentary on how authorities have applied the Recommendation in past reviews. Those tasks do not require AI to reproduce operative text verbatim, so the regime-contamination failure mode is largely neutralised. Where AI is dangerous on this regulation is exactly where it appears most useful: producing a clean, structured articulation of what a specific provision says.
That is where the EU-to-OECD substitution occurs, and that is where a verbatim cross-check is non-negotiable.
For the Legal function's internal workflow, the practical control is a document-level rule: any internal artefact that cites a specific Section IV provision by number, particularly IV.3 on remedy hierarchy, must carry a footnote tracing the citation to the primary text, and a reviewer must have confirmed that citation. This is not a new control; it mirrors what Legal already applies to national implementing legislation. Extending it explicitly to the OECD Recommendation level, and flagging the EU-OECD contamination risk in team training materials, closes the gap that this finding exposes.
How RLB Can Help
RegLeg's published Hallucination Research is available as open reference material, a pre-flight check your team can run before relying on AI output on any regulatory question touching spectrum licensing, interconnection obligations, data localisation, or lawful-intercept compliance. The research is indexed by regulatory instrument, so if your team is about to use an AI tool to summarise an ITU recommendation or a national NRA determination, you can see in advance whether that instrument's territory is one where AI tools have already demonstrated material errors. That is a faster and more defensible QA step than asking a junior to re-read the source.
Beyond the published corpus, we do bespoke regulator deep-dives calibrated to a Telecommunications legal function's actual workflow exposure. That means mapping which AI-supported tasks, drafting licence condition summaries, preparing submissions to sectoral regulators, reviewing foreign operator interconnect terms, tracking spectrum assignment conditions across multiple NRAs, carry the highest documented hallucination risk, and at what level of specificity those errors tend to appear. The output is a prioritised exposure map your team can use to set internal policy on where AI assistance is warranted without a qualified lawyer in the review chain, and where it is not.
We also offer a confidential review of your firm's existing AI-use policy against RegLeg's failure-mode catalogue. In practice, most Legal team AI policies in the sector were written before systematic failure-mode data existed; they draw lines in the wrong places. We work through the policy with you, flag the gaps relative to documented failure patterns, and produce a prioritised remediation list, not a generic risk matrix, but specific policy clauses tied to specific failure categories observed in regulatory contexts comparable to yours.
Training materials and CPD-aligned content for team rollout are available as a follow-on, built around the same findings rather than generic AI-literacy content that your senior lawyers will not find credible.