ESG & Sustainability teams at Digital Platforms & Marketplaces firms operating under digital infrastructure environmental impact and data-centre energy reporting are increasingly using AI to populate CDP submissions and investor ESG questionnaire responses with OECD-cited data-centre energy benchmarks, draft sustainability-report sections on digital-infrastructure footprint, and prepare internal carbon-accounting baselines for platform-side data-centre offtake exposures.
The OECD's 2025 Revision of the Recommendation on Digital Technologies and the Environment carries a named, citable statistic on Ireland's data-centre share of metered electricity, drawn from Ireland's Central Statistics Office, that ESG & Sustainability teams at digital platform and marketplace firms will reach for when populating sustainability disclosures, ESG investor responses, and regulatory briefings on digital-infrastructure environmental impact. That statistic is exactly the kind of figure the RLB Specialist Panel tested two frontier AI subjects against.
The RLB Specialist Panel issued a Specialist Panel application-style question on the share of Ireland's 2021 metered electricity that data centres accounted for, per the figure cited in the OECD Digital Economy Outlook 2024 chapter referenced by the 2025 Recommendation, sourced from Ireland's CSO (2023). Two frontier AI models tested by the RLB Specialist Panel returned the figure as 14 per cent and extended the answer with a four-point time series running from 5 per cent in 2015 through 21 per cent in 2023. The regulator's verbatim text records 11 per cent in 2021, with no multi-year trajectory.
The failure class is Fabricated Fact: a confidently delivered, citably attributed statistic that does not match the source document, compounded by a fabricated time series that does not appear anywhere in the OECD or CSO published record.
For ESG & Sustainability teams at digital platform and marketplace firms, this is operationally consequential because the wrong figure is not a vague paraphrase. It is delivered with a real source chain, CSO 2023 via OECD Digital Economy Outlook 2024, that survives standard reference-check review. AI tools tested by the Panel overstated Ireland's 2021 data-centre share of metered electricity as 14 per cent, attributed to Ireland's CSO via the OECD Digital Economy Outlook 2024, when the primary source records 11 per cent.
The AI also fabricated a multi-year trend series, 5 per cent rising to 21 per cent across 2015 to 2023, that does not appear anywhere in the source material. For an ESG or sustainability team at a digital platform or marketplace firm, this matters most when that figure is used as a benchmark in an environmental disclosure, an investor ESG questionnaire response, or an internal carbon-accounting baseline. The error is pre-cited with credible provenance, which means it will pass a junior review that assumes AI-supplied citations have been verified.
If the inflated figure enters a CDP submission or an investor-facing sustainability report, the firm faces the combination of a factually wrong claim and a traceable citation trail that any counterparty can check against the primary source. Correction requires identifying and retracting every downstream document that inherited the figure, a material remediation cost and a reputational exposure with investors and regulators who treat ESG disclosure accuracy as a governance signal.
The audit's finding on this question is published with an immutable RLB Citation ID. The relevant entry is RLB-H-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006-Sonnet46. The full audit is published at the OECD Digital Technologies and the Environment Recommendation (2025 Revision) hub on RegLegBrief.com.
This is the consolidated view of findings. Click the Citation IDs or 'see details →' on any item for the full details for each finding.
AI tools we tested overstated Ireland's 2021 data centre share of metered electricity as 14%, a figure attributed to Ireland's CSO via the OECD Digital Economy Outlook 2024, when the primary source states 11%. The AI also fabricated a multi-year trend series (5% / 14% / 18% / 21%) that does not appear anywhere in the source material.
For an ESG or sustainability team at a digital platform or marketplace firm, this matters most when that figure is used as a benchmark in an environmental disclosure, an investor ESG questionnaire response, or an internal carbon-accounting baseline. The error is pre-cited with credible provenance, which means it will pass a junior review that assumes AI-supplied citations have been verified.
If the inflated figure enters a CDP submission or an investor-facing sustainability report, the firm faces the combination of a factually wrong claim and a traceable citation trail that any counterparty can check against the primary source. Correction requires identifying and retracting every downstream document that inherited the figure, a material remediation cost and a reputational exposure with investors and regulators who treat ESG disclosure accuracy as a governance signal.
Every finding on this page compares an AI subject's account of the rule against the regulator's verbatim text from the regulator's own portal. Both are linked. Each delta, its root causes, and impact analysis are documented and published with immutable Citation IDs.