The AI in Business Podcast How to Leverage AI for Skill Verification - with Taylor Sullivan of Workera
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Nov 10, 2025 Taylor Sullivan, Head of Product and Assessments at Workera, dives into the world of AI-driven skills verification. He shares insights on the limitations of traditional skill inferencing methods like resumes. Discover how AI can create detailed skill taxonomies to better match candidates to roles. Taylor discusses the importance of psychometrically valid assessments for accuracy and fairness. He also highlights how verified skills data can enhance business outcomes, reduce hiring errors, and promote meritocratic practices in organizations.
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Assumptions Fail For Skill Data
- Skill inferencing uses indirect signals like resumes and project history and often produces inaccurate, assumption-based data.
- Verification replaces assumptions with measured observations, providing precise, actionable skill data for talent decisions.
Model Roles With AI For Relevant Skills
- Use AI to analyze large role datasets and rapidly build granular skill taxonomies tailored to job contexts.
- Then configure assessments that adapt to specific company and project contexts for more relevant measurement.
Measurement Science Must Underpin Assessments
- Psychometrics is the science of measurement focused on accuracy, reliability, and fairness of assessments.
- Baking psychometric practices into AI preserves measurement quality while scaling assessments across an organization.