AI Fallacies in Documentation: Lessons Learned When Automation Didn’t Deliver
- Fachvortrag
- AI and New Technologies in TC
- 22. April
- 06:30 PM (CEST) - 07:10 PM (CEST)
-
Dr. Guiseppe Getto
- Mercer University
-
Jackie Damrau
- Product Owner
Contents
If your organization rushed into using AI for documentation, you may have found that results did not match the marketing pitch. Instead of effortless drafts or a shortcut around structured content, AI often multiplies errors as quickly as it generates text.
In this session, we unpack five common AI fallacies that derail documentation efforts, ranging from treating AI as a writer rather than a collaborator to assuming prompting can replace solid content design. Our analysis is grounded in real pilot implementations and a survey of nearly 90 technical writers. We show how these misconceptions create quality, governance, and workflow issues, and how teams recover through stronger structure, metadata, and human review. Attendees will also evaluate their own readiness through a short poll and apply an AI Governance Maturity Model to improve their current practices. We focus on practical steps that any team can take immediately, including how to assess risk, strengthen oversight, and prepare documentation workflows for more sustainable and responsible uses of AI.
Takeaways
Identify five AI fallacies, assess your team's readiness, and use an AI maturity model to establish guardrails for responsible AI adoption.
Prior knowledge
Understanding of documentation workflows, content modeling, and basic exposure to generative AI tools.