What share of Ireland's 2021 metered electricity did data centres account for, per the figure cited in the OECD Digital Economy Outlook 2024 chapter (sourced from Ireland's CSO 2023)?
The model correctly identified the source chain, CSO 2023 as cited in the OECD Digital Economy Outlook 2024, but substituted 14% for the regulator's 11%. It then extended the response with a forward-projected series (18% in 2022, 21% in 2023) that is not present in the regulator's text, suggesting the model reconstructed a plausible growth trajectory rather than quoting the authoritative figure. The error is not a misidentified source but a numeric value that has drifted at the point of reproduction.
This finding implicates two distinct subsystems. First, the retrieval layer correctly surfaced the source lineage (CSO 2023 via OECD Digital Economy Outlook 2024) but the numeric payload at the point of generation drifted — suggesting the training corpus contains multiple paraphrased variants of this figure and the model resolved the conflict toward a higher value present in secondary commentary rather than the verbatim primary text.
Second, the forward-series confabulation (18% in 2022, 21% in 2023) indicates the model's generation logic treats trend continuation as a low-uncertainty extension when an anchor year and growth direction are established in context — a calibration gap that is independent of retrieval quality and would require a post-generation verification step or explicit uncertainty injection to close.
A CA/PA who accepts the AI-generated figure at face value and includes it in a client deliverable, a sustainability opinion, a due diligence memo, or a board briefing, will have signed off on a materially incorrect statistic attributed to a named official source. The client loses the ability to rely on that deliverable as an accurate benchmark. If the figure is used to contextualise a disclosure in a regulated filing or an ESG-linked transaction document, correcting the record after publication or submission is costly and reputationally damaging.
The fabricated time-series compounds the risk: it provides apparent trend evidence that may influence investment or risk-assessment conclusions drawn by the client or a counterparty reviewing the document.
Each finding has a stable Citation ID (RLB-F-… for aggregated case-study findings, RLB-H-… for raw per-model hallucinations) — like a DOI, the ID always resolves to the canonical finding even if URLs change.
RegLeg Specialist Panel (2026). "Finding#1, Ireland data-centre electricity share, fabricated percentage and time-series — Practitioners — Accountants (CA/PA)." Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006. RegLegBrief AI Hallucination Research, published 2026-06-11. https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/practitioners/accountants-ca-pa/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/
RegLeg Specialist Panel. (2026). Finding#1, Ireland data-centre electricity share, fabricated percentage and time-series [Hallucination finding RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006]. RegLegBrief AI Hallucination Research. https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/practitioners/accountants-ca-pa/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/
RegLeg Specialist Panel, Finding#1, Ireland data-centre electricity share, fabricated percentage and time-series [RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006], RegLegBrief AI Hallucination Research (June 11, 2026), https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/practitioners/accountants-ca-pa/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/.
@misc{reglegbrief_RLB_F_INT_OECD_OECD_DIGITAL_TECHNOLOGIES_ENVIRONMENT_2025_Q006,
author = {RegLeg Specialist Panel},
title = {Finding#1, Ireland data-centre electricity share, fabricated percentage and time-series},
year = {2026},
publisher = {RegLegBrief AI Hallucination Research},
note = {Hallucination finding Citation ID: RLB-F-INT-OECD-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-Q006},
url = {https://reglegbrief.com/regulators/j1/int/OECD/OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025/practitioners/accountants-ca-pa/finding/INT-OECD-INT-001-OECD-DIGITAL-TECHNOLOGIES-ENVIRONMENT-2025-v1-006/}
}
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.