“Wikipedia Bans AI-Generated Content,” or some variation of that headline, captured online newsfeeds on March 26, 2026. But Wikipedia’s announcement, while consequential (impacting 7.1 million articles), wasn’t that unusual.
In 2025, several large publishers released policies governing the use of generative AI (genAI) in content development and editorial workflows. Organizations such as Elsevier, John Wiley & Sons, and SAGE Publishing recognized the growing reality: AI-assisted content creation had already entered the workplace, often faster than governance and guidance could keep pace.
The concern is practical rather than theoretical. GenAI tools introduced new questions about factual accuracy, fabricated citations, copyright exposure, confidential data, manipulated images, and growing challenges with authorship and ownership.
Small companies and organizations outside the publishing industry face many of these same risks.
A content department generating online content through AI prompts, a software company creating AI-assisted chatbots, or a nonprofit drafting donor communications with AI tools all face important questions:
- What kinds of AI use are acceptable?
- What kinds of AI use should be restricted or prohibited?
- When should AI use be disclosed?
- Who remains responsible for validating accuracy?
- How should confidential information be protected?
For content managers and project managers, particularly in organizations that outsource content creation, an AI policy for content contributors is more than a legal safeguard. It is a governance tool that helps preserve content quality, establish accountability, and maintain trust with audiences. In this blog post, I outline the key elements of AI policy.
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