Rethinking Skills and Innovation in the Digital Transformation Era

Digital transformation and Artificial Intelligence are reshaping innovation processes while placing renewed emphasis on the skills required to generate and govern technological change. This editorial argues that skills remain under-theorised in R&D management despite their growing relevance for firms, policymakers, and societies. Building on contributions to the Special Issue, we propose a multi-level framework linking individual abilities, organisational capabilities, and macro-level human capital. The framework conceptualises skills as both antecedents and outcomes of innovation, co-evolving with digital technologies through cross-level mechanisms, including policy drivers, organisational learning, capability renewal, systemic spillovers, and societal upgrading. We identify key conceptual, methodological, and empirical blind spots, including static views of skills, limited longitudinal evidence, outdated indicators, and insufficient attention to hybrid skill profiles. We conclude by outlining a research agenda that calls for co-evolutionary models, real-time data infrastructures, advanced methods, firm–university data partnerships, and updated measurement frameworks to strengthen the study of skills and innovation in the digital transformation era.