Observed Signal · Jun 13, 2026 · Report Withdrawal · Source: techcrunch · Impact: 3/5 · Sentiment: Negative
KPMG Withdraws AI Report After Hallucination Errors
KPMG has removed a report titled "Redefining excellence in the age of agentic AI" after research group GPTZero and several organisations flagged factual inaccuracies the report attributed to their AI use. The report, originally published in October 2025, was found to contain errors that GPTZero and the Financial Times said likely stemmed from AI hallucinations. UBS, the UK’s National Health Service, Swiss Federal Railways and Transport for London told the FT the report’s claims about their AI usage were incorrect or misleading. KPMG said it pulled the document from its websites while it conducts an internal investigation and reiterated its guidelines requiring human oversight of AI-generated content. The article notes a similar recent withdrawal by EY over AI-related errors.
A major professional-services firm removed an AI report after hallucination-driven inaccuracies were identified; this undermines trust in AI-generated research and highlights the need for human oversight and verification across enterprises and consultancies.
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Key Takeaways & Evidence Grounding
- KPMG removed a report titled "Redefining excellence in the age of agentic AI" from its websites while investigating apparent inaccuracies.
- The report was published in October 2025.
- Research group GPTZero identified a number of inaccuracies and told the Financial Times the errors appeared to stem from AI hallucinations.
- UBS, the UK’s National Health Service, Swiss Federal Railways and Transport for London said the report’s claims about their AI usage were untrue or misleading.
- EY withdrew a separate report the previous month after it appeared to include fake footnotes and AI hallucinations.
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KPMG Withdraws AI-Agents Report Over Hallucinated Case Studies
KPMG has withdrawn an October report titled "Exzellenz im Zeitalter agentischer KI neu definieren" after it was found to contain hallucinated case studies and false claims about organizations including UBS, the Swiss Federal Railways (SBB) and the UK National Health Service. UBS and SBB told the Financial Times the report’s statements about their use of AI agents were factually incorrect, prompting KPMG to remove the paper from multiple websites and launch an internal investigation. The episode follows a recent EY retraction for fabricated data and nonexistent citations. Independent detector GPTZero flagged the KPMG report’s hallucinations, and separate academic research has identified tens of thousands of fake citations in published papers, underscoring growing concerns about AI-generated misinformation and the reputational and practical risks of unverified AI‑sourced content.
Three Examples of AI Hallucinations in 2026
Gary Marcus published an opinion post on Substack (June 12, 2026) highlighting three recent examples of generative AI 'hallucinations.' The piece references an Anne Applebaum X post that calls out a KPMG report whose business case studies reportedly contained AI-generated fabrications, and cites follow-ups from 404 Media and a submission from Valerio Capraro as additional instances. Marcus uses these cases to illustrate ongoing gaps between the capabilities and the claimed reliability of contemporary large language models. The article is commentary rather than a technical or investigative report and appears on Marcus’s Substack newsletter.
Trusted Brands Amplify Harm When AI Is Confidently Wrong
An opinion piece argues that product teams are increasingly tempted to surface AI systems under trusted brand names in ways that preempt user skepticism, risking large reputational and legal damage when those systems confidently produce false information. The author highlights psychological drivers—authority bias, status-enhancement and automation bias—and cites real-world examples (Google Bard’s demo error, an Air Canada chatbot tribunal, fake legal citations arising from ChatGPT) plus academic research showing AI models can grow more confident as they make mistakes. The article recommends meaningful human oversight with real accountability (people with reputational or professional stakes) and cites the EU AI Act’s requirement for measurable human intervention in high-risk systems.
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