From Problem to Solution: A Case Study Approach to Using AI in Genealogy

Andrew Redfern
Jan 7, 2026
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SyllabusSyllabus
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About this webinar

Artificial intelligence is changing the way genealogists work—but how do you move beyond tips and tricks to apply AI in a sound, methodical way? In this session, Andrew Redfern demonstrates how a case study approach provides the answer. Using real examples, he walks through the stages of tackling a genealogical problem with AI, showing how tools can assist with transcription, analysis, correlation of evidence, and presentation of findings. Rather than treating AI as a shortcut, Andrew highlights how to integrate it into the established genealogical research cycle—problem definition, source gathering, analysis, and conclusion. Attendees will see how AI can clarify complex evidence, save time on repetitive tasks, and support storytelling, while still requiring human expertise and critical thinking. By the end of the session, participants will have a practical framework they can adapt to their own research problems, ensuring that AI becomes a trusted partner in genealogical methodology.

About the speaker

Andrew Redfern is an enthusiastic family historian and accomplished speaker, having delivered presentations both in his home country of Australia and internationally over many years. His innovative wo...
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Key points and insights

Genealogy research rarely follows a tidy, linear path—and this Legacy Family Tree Webinars session leans into that reality. In “From Problem to Solution: A Case Study Approach to Using AI in Genealogy,” Andrew Redfern demonstrates how artificial intelligence can support real research work: sorting messy evidence, surfacing hidden clues, and clarifying next steps when records conflict or go missing. Rather than treating AI as a tool for polishing a finished narrative, the webinar shows how to use it as a thinking partner throughout the investigative process—especially helpful for brick walls, incomplete timelines, and documents that still hold untapped details.

  • A practical research cycle replaces “ask-and-accept” searching. The webinar centers on a repeatable four-step method—assemble, analyze, question, plan—that mirrors strong genealogical practice while making the researcher’s reasoning more explicit and trackable.

  • AI becomes most valuable during research, not after it. Live examples show how AI can help transcribe and mine letters for genealogically relevant details, flag inconsistencies (such as locations and timeframes), and transform narrative material into structured timelines—without skipping straight to conclusions.

  • Different problem types call for different AI tactics. Beyond narrative sources, the session illustrates how structured reports can be audited for missing fields, and how conflicting evidence (such as mismatched baptisms or dates) can be approached with targeted questions that keep the process evidence-led instead of assumption-driven.

The full webinar is worth viewing for the step-by-step demonstrations, prompt examples, and the “researcher mindset” that keeps AI outputs in their proper place: helpful suggestions that still require human judgment, source evaluation, and follow-up work. Watching the complete recording also reveals how small prompt adjustments can prevent distractions (like premature “polishing”) and keep efforts focused on solving the underlying research problem. To extend the learning, the syllabus materials provide additional guidance—including a reusable worksheet designed to support repeated use of the cycle across multiple ancestors—making it easier to apply these methods to current projects and long-standing brick walls.

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