Refers to the practice of identifying, searching for, extracting, or inferring specific skills from individuals, job postings, resumes, educational records, digital profiles, work histories, or labor market data for hiring, workforce planning, talent matching, or workforce analytics purposes.

Skills fishing typically involves employers, recruiters, platforms, or AI systems attempting to identify transferable, adjacent, hidden, emerging, or partially documented skills that may not be visible through traditional job titles, degrees, or resumes. Examples include AI systems scanning resumes to infer skills not explicitly listed, platforms matching workers to jobs based on inferred competencies, employers searching internal workforce data to identify employees with transferable skills, and talent marketplaces identifying workers who could transition into adjacent occupations.

The term is increasingly used in discussions about skills-first hiring, AI-driven recruiting, talent intelligence systems, labor market analytics, workforce platforms, credential matching, and automated skills extraction technologies.  The term may be used positively to describe broader talent discovery and workforce mobility opportunities. The term may also be used more cautiously to describe overly broad AI-driven candidate searching, aggressive talent mining, excessive workforce surveillance, or systems that infer skills without sufficient transparency or accuracy.