The collection, analysis, interpretation, and use of information about skills to understand the skills that people and workforces have, the skills employers and labor markets need, gaps or mismatches between skills supply and demand, and how skill requirements are changing over time.

Skills intelligence typically draws on multiple sources, including skills assessments, job postings, occupational and labor-market data, employee profiles and work histories, credentials and learning records, skills taxonomies, employer information, and workforce analytics. Artificial intelligence and other data-analysis technologies are increasingly used to identify patterns, map relationships among skills and occupations, assess current capabilities, and anticipate emerging skill needs.

Skills intelligence can be used at multiple levels:

• Employers - to inform hiring, workforce planning, learning and development, upskilling and reskilling, internal mobility, project staffing, and organizational transformation.
• Education and workforce organizations - to align programs with changing skill needs.
• Governments, researchers, and policymakers - to identify labor-market trends, anticipate skill shortages and mismatches, and inform education, training, workforce, and economic-development policies.