A recent KPMG report on agentic AI contained approximately 40 AI hallucinations among its 45 citations, leading to its immediate withdrawal. Major entities like UBS, the UK’s National Health Service, Swiss Federal Railways, and Transport for London publicly refuted claims about their AI usage, stating they were untrue or misleading. This widespread repudiation prompted KPMG to pull the study.
KPMG, positioned as an expert on AI, published a report on agentic AI that was so riddled with inaccuracies and AI hallucinations it had to be withdrawn. This incident reveals a critical vulnerability in how even leading consulting firms manage AI-generated content.
Rigorous human oversight and verification are critically needed in an age where even professional services firms are struggling to manage AI-generated content, potentially eroding trust in expert analysis.
What We Know About KPMG's Withdrawn AI Report
- KPMG withdrew its report titled “Redefining excellence in the age of agentic AI” due to untrue claims about AI usage, according to TechCrunch.
- The study on agentic AI was officially titled ‘Total Experience: Redefining Excellence in the Age of Agentic AI’, according to The Indian Express.
- UBS, the UK’s National Health Service, Swiss Federal Railways, and Transport for London stated the report's claims about their AI usage were untrue or misleading, according to TechCrunch and The Indian Express.
- The KPMG report falsely claimed Japanese East Japan Railway Company (JR East) uses agentic AI for customer service, according to PCMag.
- This specific claim linked to an unrelated 2019 press release, according to PCMag.
- KPMG’s withdrawal followed external researchers identifying significant inaccuracies.
Are AI Hallucinations Impacting Business Reports in 2026?
KPMG’s report contained approximately 40 AI hallucinations among its 45 citations, a significant failure in factual accuracy. GPTZero researchers found that only 5 out of 45 citations in the KPMG report correctly pointed to the cited source. Only 5 out of 45 citations in the KPMG report correctly pointed to the cited source, suggesting a systemic breakdown in verification.
The report also falsely claimed Austrian electricity provider Verbund uses AI agents in households for real-time analytics as part of its 'energy-as-a-service ecosystem'. Furthermore, a statistic in the KPMG report stated over 55 percent of CEOs ranked AI as their top investment priority, contradicting KPMG's own 2025 CEO Outlook which reported 71 percent, according to The Indian Express and The Register. The contradiction between the report's 55 percent statistic and KPMG's own 2025 CEO Outlook of 71 percent indicates a failure to cross-reference even the firm's proprietary data.
Given that GPTZero researchers found only 5 out of 45 citations were correct, companies relying on 'expert' AI reports risk basing strategic decisions on dangerously fabricated information. The KPMG report's contradiction of its own 2025 CEO Outlook data (55% vs. 71% for AI as top priority) underscores that even leading firms are failing to implement basic internal verification for AI-generated content, making their advice on AI inherently untrustworthy.
Evolving AI Usage Trends: What the 2026 KPMG Report Implies
The sheer scale of fabrication, with 40 out of 45 citations being false or misleading, signals that KPMG's internal review processes for AI-generated content were either non-existent or catastrophically ineffective. False claims about major public and private entities like UBS, NHS, and JR East directly undermine KPMG’s credibility in AI expertise.
The report's false claims about 'agentic AI' usage, sometimes linking to unrelated older press releases, reveal AI isn't just inventing facts. It creatively misinterprets existing data, making human verification more complex than simply checking for outright fabrication. AI creatively misinterpreting existing data, making human verification more complex than simply checking for outright fabrication, requires deep domain expertise to prevent its spread.
The false claims about major entities like UBS, NHS, and JR East, sometimes linked to irrelevant older press releases, demonstrate that AI-generated content requires a level of human scrutiny far beyond simple spell-checking, demanding deep domain expertise to prevent the spread of sophisticated misinformation.
Mitigating AI Hallucinations: Strategies for 2026
External researchers from GPTZero quickly identified that only 5 out of 45 citations were correct, suggesting KPMG's internal vetting process for a high-profile AI report was either rushed or entirely bypassed. The rapid external exposure, where GPTZero researchers quickly identified that only 5 out of 45 citations were correct, highlights the immediate need for robust, human-led verification frameworks.
Skeptics of uncritical AI adoption and researchers like GPTZero emerged as winners in this scenario, validating their calls for greater scrutiny. KPMG, however, faces significant damage to its reputation and credibility, as do companies falsely implicated by the report's inaccuracies. The broader perception of AI's reliability without proper vetting also suffers.
Firms must integrate domain experts to cross-reference AI outputs against proprietary data and external sources. Integrating domain experts to cross-reference AI outputs against proprietary data and external sources prevents reputational damage and the spread of misinformation. By Q3 2026, consulting firms failing to implement these stringent controls risk significant client distrust and market share erosion.
What are the latest findings on AI hallucinations in 2026?
The KPMG incident revealed that AI hallucinations can extend beyond general factual errors to include specific, fabricated company usage data and internal contradictions with a firm's own survey results. This complexity demands a verification process that checks for both external accuracy and internal consistency.
How is AI usage evolving according to the 2026 KPMG report?
The withdrawn KPMG report attempted to highlight the perceived evolution towards "agentic AI" systems in business, suggesting autonomous AI agents were increasingly deployed. However, the report's inaccuracies mean its specific claims about this evolution, such as Verbund's energy-as-a-service ecosystem, were unreliable and lacked factual basis.
What are the risks of AI hallucinations in business?
Beyond damaging the publishing firm's reputation, AI hallucinations in business reports can lead clients to make strategic decisions based on fabricated data. For instance, false claims about competitor AI adoption could prompt misguided investments or misallocation of resources, potentially causing significant financial losses or missed opportunities.
