AI Explored Personalizing AI for a Business: Turning Generic Tools into Customized Solutions
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Jan 13, 2026 
Taylor Radey, Director of Research at SmarterX and instructor at the AI Academy, shares her insights on personalizing AI for businesses. She discusses the pitfalls of relying on generic AI outputs, emphasizing the importance of strategic personalization. Taylor introduces her D-A-T-A framework for capturing unique business insights and shares tools for extracting knowledge from experts. She also explains how to create custom AI agents and maintain knowledge bases, highlighting ways to enhance efficiency and trust in AI applications.
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Default AI Tends Toward Average
- Generative AI defaults to producing predictable, average outputs because it replicates patterns from its training data.
- Taylor Radey warns this leads companies to sound the same unless they personalize their AI.
Start By Capturing Proprietary Knowledge
- Capture and collect all unstructured company knowledge like SOPs, frameworks, and testimonials before building AI tools.
- Use the D.A.T.A. framework: Domain, Approach, Talent, Accomplishments to guide what to capture.
Use Voice To Extract Tacit Knowledge
- Extract expertise from people using voice: record interviews, meetings, and sales calls to capture natural, fast speech.
- Use transcription tools to convert those recordings into searchable, authentic source material.