Beyond automation and augmentation: reframing innovation policy for the work in the age of AI

Abstract Debates over whether artificial intelligence (AI) will automate or augment human labour remain deeply polarized. While one view warns of large-scale technological unemployment, the other emphasizes productivity gains from human–machine collaboration. This paper argues that both perspectives capture complementary dimensions of the same transformation and introduces a job-contents perspective that disaggregates occupations into tasks and skills. From this viewpoint, AI selectively automates certain tasks within occupations, reshaping the structure of work and the organization of skills. The paper outlines key policy directions to enhance adaptability in the AI era. It further proposes the Job Content Observatory, an international framework that integrates public and private labour data with information on technological trends to monitor real-time transformations in tasks and skills and to support evidence-based innovation policy.