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Briefings Blog

The running blog from the RLB Specialist Panel delves into real-world scenarios where the compliance, legal, or AI lab team interacts with frontier AI models under specific regulations. The blogs are anonymised to remove client-specific details and include insights from the RLB team analysing the hallucinations experienced in AI models while working on these cases. For example, when a model returns a confident answer that contradicts the regulator's primary text, such as a fabricated staff letter, a wrong appendix, or an inverted scope, these issues are discussed here. Each blog explains one set of findings and what it would have meant for the team that would have acted on it, sans this research initiative. This blog is frequently updated, a few times a day.

263 briefings in the archive · Subscribe via Atom: /briefings/feed.xml (this blog) · /feed.xml (all RegLegBrief publications)
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Showing 5 of 263 · page 30 of 53
Tuesday, 29 September 2026
Sector: Mainboard / Premium-Listed Issuers and Dept: Legal INT OECD

Mainboard / Premium-Listed Issuers Legal teams: documentation and reporting gaps possible from AI reading of Recommendation of the Council on Merger Review

For Mainboard / Premium-Listed Issuers Legal teams working with Recommendation of the Council on Merger Review (2025 Revision): Specialist-Panel-verified findings on where AI summaries diverge from the regulator's...

Legal teams at mainboard and premium-listed issuers approaching announceable transactions that engage the 2025 OECD Merger Review Recommendation are increasingly using AI to draft board memos on merger-clearance exposure, generate disclosure-committee briefings on the operative-section structure, and validate Section-level citation language in announcement documents and regulator-facing engagement papers.

The RLB Specialist Panel put a set of practitioner-grade questions on the 2025 OECD Merger Review Recommendation to two frontier AI models with web search active. Each question is prepared by the Panel based on the workflows that legal teams at mainboard and premium-listed issuers actually use AI for under the OECD's 2025 revision of the Recommendation of the Council on Merger Review (OECD/LEGAL/0333). The Panel then binds every AI response to verbatim regulator-issued source text held as primary substrate.

On the 2025 OECD Merger Review Recommendation, the AI subjects returned two hallucinated answers for legal teams at mainboard and premium-listed issuers, in the form of Structure Inflation.

For legal teams at mainboard and premium-listed issuers advising on cross-border merger transactions touching the 2025 OECD Merger Review Recommendation, citation accuracy on the operative architecture, on Section IV.3 remedies hierarchy, and on Section III.11.b failing firm defence is load-bearing in every authority-facing submission, every board memo, and every transactional document. A counterparty or competition authority who identifies a structural inflation, a misattributed sub-hierarchy, or a closed-cumulative-test framing on first reading calls the entire piece of advice into question.

The structural-architecture failure is the most directly visible: a board memo or regulator-facing submission that lists 'international co-operation' or 'monitoring' as operative RECOMMENDS sections is wrong on first reading. The Section IV.3 EU sub-hierarchy import is the most insidious failure, reading as authoritative because the EU framework is real, but presenting EU practice as OECD content imports the wrong normative baseline into the firm's remedy strategy.

The published Specialist Panel findings carry the following citation identifiers:

Sector: Private Equity & Venture Capital and Dept: Legal INT OECD

Private Equity & Venture Capital Legal teams: documentation and reporting gaps possible from AI reading of Recommendation of the Council on Merger Review

For Private Equity & Venture Capital Legal teams working with Recommendation of the Council on Merger Review (2025 Revision): Specialist-Panel-verified findings on where AI summaries diverge from the regulator's...

Legal teams at private equity and venture capital sponsors evaluating cross-border control transactions under the 2025 OECD Merger Review Recommendation are increasingly using AI to draft investment-committee memos on merger-clearance exposure, generate deal-team briefings on the failing firm defence and remedies hierarchy, and validate the operative-section structure of the Recommendation against the OECD text before commitment papers issue.

The RLB Specialist Panel put a set of practitioner-grade questions on the 2025 OECD Merger Review Recommendation to two frontier AI models with web search active. Each question is prepared by the Panel based on the workflows that legal teams at private equity and venture capital sponsors actually use AI for under the OECD's 2025 revision of the Recommendation of the Council on Merger Review (OECD/LEGAL/0333). The Panel then binds every AI response to verbatim regulator-issued source text held as primary substrate.

On the 2025 OECD Merger Review Recommendation, the AI subjects returned four hallucinated answers for legal teams at private equity and venture capital sponsors, in the form of Structure Inflation, Misattributed Cross-Jurisdictional Doctrine, and Inter-Alia-to-Closed-Test Conversion.

For legal teams at private equity and venture capital sponsors advising on cross-border merger transactions touching the 2025 OECD Merger Review Recommendation, citation accuracy on the operative architecture, on Section IV.3 remedies hierarchy, and on Section III.11.b failing firm defence is load-bearing in every authority-facing submission, every board memo, and every transactional document. A counterparty or competition authority who identifies a structural inflation, a misattributed sub-hierarchy, or a closed-cumulative-test framing on first reading calls the entire piece of advice into question.

The structural-architecture failure is the most directly visible: a board memo or regulator-facing submission that lists 'international co-operation' or 'monitoring' as operative RECOMMENDS sections is wrong on first reading. The Section IV.3 EU sub-hierarchy import is the most insidious failure, reading as authoritative because the EU framework is real, but presenting EU practice as OECD content imports the wrong normative baseline into the firm's remedy strategy.

The published Specialist Panel findings carry the following citation identifiers:

Sector: Investment Banking and Dept: Legal INT OECD

Investment Banking Legal teams: documentation and reporting gaps possible from AI reading of Recommendation of the Council on Merger Review

For Investment Banking Legal teams working with Recommendation of the Council on Merger Review (2025 Revision): Specialist-Panel-verified findings on where AI summaries diverge from the regulator's text, and what...

Legal teams at investment banks advising on M&A transactions engaging the 2025 OECD Merger Review Recommendation are increasingly using AI to draft counsel-facing memos on the operative-section structure, generate transaction-committee briefings on the remedies-hierarchy and failing-firm-defence positions, and validate OECD citation language in deal-clearance representations to authorities and to counterparties.

The RLB Specialist Panel put a set of practitioner-grade questions on the 2025 OECD Merger Review Recommendation to two frontier AI models with web search active. Each question is prepared by the Panel based on the workflows that legal teams at investment banking firms actually use AI for under the OECD's 2025 revision of the Recommendation of the Council on Merger Review (OECD/LEGAL/0333). The Panel then binds every AI response to verbatim regulator-issued source text held as primary substrate.

On the 2025 OECD Merger Review Recommendation, the AI subjects returned four hallucinated answers for legal teams at investment banking firms, in the form of Structure Inflation, Misattributed Cross-Jurisdictional Doctrine, and Inter-Alia-to-Closed-Test Conversion.

For legal teams at investment banking firms advising on cross-border merger transactions touching the 2025 OECD Merger Review Recommendation, citation accuracy on the operative architecture, on Section IV.3 remedies hierarchy, and on Section III.11.b failing firm defence is load-bearing in every authority-facing submission, every board memo, and every transactional document. A counterparty or competition authority who identifies a structural inflation, a misattributed sub-hierarchy, or a closed-cumulative-test framing on first reading calls the entire piece of advice into question.

The structural-architecture failure is the most directly visible: a board memo or regulator-facing submission that lists 'international co-operation' or 'monitoring' as operative RECOMMENDS sections is wrong on first reading. The Section IV.3 EU sub-hierarchy import is the most insidious failure, reading as authoritative because the EU framework is real, but presenting EU practice as OECD content imports the wrong normative baseline into the firm's remedy strategy.

The published Specialist Panel findings carry the following citation identifiers:

Sector: Law Firms and Dept: Legal INT OECD

Law Firms Legal teams: documentation and reporting gaps possible from AI reading of Recommendation of the Council on Merger Review

For Law Firms Legal teams working with Recommendation of the Council on Merger Review (2025 Revision): Specialist-Panel-verified findings on where AI summaries diverge from the regulator's text, and what that means...

Legal teams at law firms advising on cross-border merger transactions touching the 2025 OECD Merger Review Recommendation are increasingly using AI to draft client memos on the Recommendation's operative architecture, generate partner-level briefings on the remedies hierarchy and failing firm defence, and validate Section-level citation language in regulatory submissions, transactional documents, and authority-engagement papers.

The RLB Specialist Panel put a set of practitioner-grade questions on the 2025 OECD Merger Review Recommendation to two frontier AI models with web search active. Each question is prepared by the Panel based on the workflows that legal teams at law firms actually use AI for under the OECD's 2025 revision of the Recommendation of the Council on Merger Review (OECD/LEGAL/0333). The Panel then binds every AI response to verbatim regulator-issued source text held as primary substrate.

On the 2025 OECD Merger Review Recommendation, the AI subjects returned five hallucinated answers for legal teams at law firms, in the form of Structure Inflation, Misattributed Cross-Jurisdictional Doctrine, Open-Interval Collapse, and Inter-Alia-to-Closed-Test Conversion.

For legal teams at law firms advising on cross-border merger transactions touching the 2025 OECD Merger Review Recommendation, citation accuracy on the operative architecture, on Section IV.3 remedies hierarchy, and on Section III.11.b failing firm defence is load-bearing in every authority-facing submission, every board memo, and every transactional document. A counterparty or competition authority who identifies a structural inflation, a misattributed sub-hierarchy, or a closed-cumulative-test framing on first reading calls the entire piece of advice into question.

The structural-architecture failure is the most directly visible: a board memo or regulator-facing submission that lists 'international co-operation' or 'monitoring' as operative RECOMMENDS sections is wrong on first reading. The Section IV.3 EU sub-hierarchy import is the most insidious failure, reading as authoritative because the EU framework is real, but presenting EU practice as OECD content imports the wrong normative baseline into the firm's remedy strategy.

The published Specialist Panel findings carry the following citation identifiers:

Monday, 28 September 2026
Practitioner: Accountants (CA/PA) INT OECD

Accountants (CA/PA): AI summaries of Recommendation of the Council on Merger Review may understate professional obligations

For Accountants (CA/PA) working with Recommendation of the Council on Merger Review (2025 Revision): where Specialist-Panel-verified divergences between frontier AI summaries and the regulator's primary source can...

Accountants advising on cross-border merger reviews engaged with the 2025 OECD Merger Review Recommendation are increasingly using AI to draft client briefings on transaction-screening obligations, prepare partner-level summaries of the failing firm defence evidentiary standard, and validate operative-section citations against the OECD text before signing financial-suitability opinions or transaction-cost reviews.

The RLB Specialist Panel put a set of practitioner-grade questions on the 2025 OECD Merger Review Recommendation to two frontier AI models with web search active. Each question is prepared by the Panel based on the workflows that accountants actually use AI for under the OECD's 2025 revision of the Recommendation of the Council on Merger Review (OECD/LEGAL/0333). The Panel then binds every AI response to verbatim regulator-issued source text held as primary substrate. On the 2025 OECD Merger Review Recommendation, the AI subjects returned a single hallucinated answer for accountants, in the form of Inter-Alia-to-Closed-Test Conversion.

For accountants advising on cross-border merger transactions that engage the 2025 OECD Merger Review Recommendation, the operative-section structure of the Recommendation, the failing-firm-defence evidentiary standard, and the Council-reporting cadence drive transaction-suitability opinions, due-diligence reports, and inter-agency-engagement memos. A financial-suitability opinion that frames the failing-firm-defence under a closed three-condition cumulative test produces wrong client guidance on whether the defence is worth running and on what evidence to commission. A transaction-cost review that mis-states the operative section count signals to the partner and to the client that the underlying regulatory map is unreliable, which puts the entire engagement at risk.

The published Specialist Panel findings carry the following citation identifiers:

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