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The introductory article to the special issue “Labour Market in the Context of Technological Transformations” presents an overall picture of the latest technological trends altogether referred to as the Fourth Industrial Revolution (Industry 4.0), their impact on the changing structure of the labour market, the demand for prospective skills, as well as emerging policy challenges. The author concludes that ensuring the resilience, adaptability and efficiency of labour markets are therefore not only a matter of addressing the skills needs of the Next Production Revolution, but also a prerequisite to social stability and cohesion.

The “policy mix” concept has gained popularity among science, technology and innovation policy communities over the past two decades in a context of growing policy complexity and need for policy evidence. Pressing societal challenges are also prompting governments to rethink policy making in order to better align public intervention across policy domains and leverage the transformative potential of system innovations. Governments faced multiple obstacles in implementing a policy mix approach in policy making and evaluation. Based on a comparative analysis of international STI policy repositories, a conceptual framework is proposed, as well as structuring principles and operational guidelines for mapping the composition of a policy mix, identifying interactions among components and translating the mapping into measurement. In that view, a range of new policy mix metrics is introduced. Finally, the discussion focuses on the need for moving towards a new data management paradigm and enlarging the measurement mix.

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Business adoption of artificial intelligence has markedly accelerated in 2023-24, with generative AI. Some places, sectors and firms have been faster in the uptake, so that gaps are forming and reinforcing existing cleavages. AI champions have stood out in the most innovative countries and regions, among larger firms and in knowledge-intensive services. AI is being used as a business solution for greater competitiveness. Applications are manifold and context-specific, often tied to local conditions for diffusion. Legal and data protection concerns, alongside skills shortages, cost or technology lock-ins, can slow adoption though, contributing to emerging divides.