KPMG Report Allegedly Included Hallucinated Citations and Inaccurate Agentic AI Case Studies

October 28, 2025

In October 2025, KPMG published “Total Experience: Redefining Excellence in the Age of Agentic AI”. GPTZero later reported that only five of 45 citations accurately matched their sources, while others contained flawed details. The pattern reportedly suggested an unverified LLM research tool, but the system and extent of AI involvement remain unconfirmed. …through contributors—JOIN US—to learn more.

Matched TAIM controls

Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls

MAP 5.1 — similarity 0.709, rank 1. TAIM detail and related incidents →
MAP 4.1 — similarity 0.680, rank 2. TAIM detail and related incidents →
MAP 4.2 — similarity 0.679, rank 3. TAIM detail and related incidents →

Alleged deployer: kpmg, big-four-consulting-firms
Alleged developer: large-language-model-developers, generative-ai-developers, ai-research-tool-developers
Alleged harmed parties: ubs, transport-for-london, transit-systems, swiss-federal-railways, researchers, policy-analysts, nhs-greater-manchester, healthcare-organizations, financial-institutions, epistemic-integrity

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Source

Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/1563

Data source

Incident data is from the AI Incident Database (AIID).

When citing the database as a whole, please use:

McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.

Pre-print on arXiv · Database snapshots & citation guide

We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.