The State of Hallucinations in AI-Driven Insights

The rise of large language models (LLMs) is transforming how research teams generate insights. But with that transformation comes a foundational risk: hallucinations – when AI outputs sound accurate but are actually fabricated, misleading, or unverified. 

This white paper explores: 

  • What hallucinations are, and why they’re especially dangerous in the context of research 
  • The technical and operational safeguards top teams are implementing 
  • Practical questions insight leaders should ask before trusting AI with high-stakes outputs 

The goal is not to reject AI, but to embed it responsibly. As enterprises move toward automation and scale, trust and transparency must become first-class features in every research workflow.