The rapid diffusion of Artificial Intelligence (AI) across industries has intensified debates on the future of work, often framed in terms of large-scale job displacement and technological substitution. However, emerging evidence suggests that AI’s impact on employment is more nuanced, operating primarily at the task and role level rather than through the outright elimination of jobs. This study examines the relationship between AI adoption and job restructuring across industries, with specific emphasis on whether AI leads to role hybridisation rather than simple substitution. Grounded in task-based theories of technological change and socio-technical systems perspectives, the research seeks to empirically test the proposition that AI reconfigures existing job roles by recombining human and machine capabilities.

The study uses primary data generated through a structured survey administered to senior HR leaders and Heads of HR in private-sector organisations across multiple industries, including finance, information technology, manufacturing, healthcare, and services. HR leaders are uniquely positioned to provide organisational-level insights into changes in job design, task allocation, and workforce restructuring resulting from AI adoption. The survey instrument operationalises key constructs such as AI adoption intensity, task automation, role hybridisation, role substitution, and observable job restructuring outcomes, enabling systematic comparison across industries and organisational contexts.