Governing AI-Generated Content
Reduce, detect and manage hallucination risk, with evidence.
How to reduce, detect and manage hallucination risk, with a control framework, a fact-checking workflow, and a maturity model for security, risk and technology leaders.
02Use this paper when
Scenarios where this briefing earns its place on the desk.
- 01AI-generated content is entering customer communications, filings or board papers
- 02You need a layered control framework for generative AI output
- 03A fact-checking or verification workflow is being designed
- 04The board has asked how AI-content risk is governed and evidenced
- 05You are setting a maturity target for AI-content governance
03What you'll find inside
What the briefing covers, section by section.
- SECTIONWhy this is now a board-level issue
- SECTIONWhat we mean by AI-generated content
- SECTIONWhy hallucination happens
- SECTIONWhy hallucination matters
- SECTIONCommon failure scenarios
- SECTIONA control framework for reducing hallucination
- SECTIONSpecific controls to implement
- SECTIONA practical fact-checking workflow
- SECTIONPeople, process and technology
- SECTIONWhat boards and executives should ask
- SECTIONA phased implementation roadmap
- SECTIONA maturity model, plus control checklist and source notes
AUTHOR
Paul Jolliffe
FOUNDER · INFOSECAI · MBA · CISSP · ISO 27001:2022 LA / LI / IA · PRINCE2 Practitioner
Twenty years of senior security leadership across financial services, healthcare, government, telecoms and technology. Independent UK practice founded 2025. Author of the InfoSecAI insights library.
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