Empowering Human Agency in AI-Augmented Futures of Work
The EMANAIRE network will train 15 doctoral fellows to study and shape the augmented organisation - workplaces in which agentic and generative AI changes how people decide, collaborate and build capability. EMANAIRE embeds comparative longitudinal research in eight European countries and examines different organisational settings, including public administration, technology, manufacturing, and creative industries. It responds to a practical question: how to design, govern and implement augmentation so that strategy, everyday work and long-term capability co-evolve. The programme targets four interlocking tensions in responsible AI integration: top-down governance; bottom-up workflow change; social distribution and team dynamics; and temporal consequences for skills and careers. The doctoral network will study how leadership practices and decision structures adapt, how AI systems become embedded in workflows, how augmentation affects dependencies and team collaboration, and it will trace shifting skill requirements to produce clearer maps of emerging role families and career pathways. Results will be translated into empirically grounded guidance, such as diagnostic tools, practical recommendations and capability frameworks. These will be developed in collaboration with employers, unions and public bodies. Training brings together advanced empirical methods, human-centred design, socio-technical analysis and intersectoral secondments, all supported by a shared measurement strategy and transparent research practices. Through comparative studies, multi-level instruments and longitudinal data, the network will generate governance models, workflow insights, indicators of team interaction, and evidence on career development that can be applied across sectors. EMANAIRE aligns with European priorities on trustworthy, human-centred AI and contributes to the UN SDGs on decent work and industry, graduating researchers for trustworthy, inclusive and sustainable augmentation.
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Imported from OpenAIRE Germany | Grant 101311637.
Open sourceOverview
Grant agreement 101311637 | EMANAIRE
Open sourceThe EMANAIRE network will train 15 doctoral fellows to study and shape the augmented organisation - workplaces in which agentic and generative AI changes how people decide, collaborate and build capability. EMANAIRE embeds comparative longitudinal research in eight European countries and examines different organisational settings, including public administration, technology, manufacturing, and creative industries. It responds to a practical question: how to design, govern and implement augmentation so that strategy, everyday work and long-term capability co-evolve. The programme targets four interlocking tensions in responsible AI integration: top-down governance; bottom-up workflow change; social distribution and team dynamics; and temporal consequences for skills and careers. The doctoral network will study how leadership practices and decision structures adapt, how AI systems become embedded in workflows, how augmentation affects dependencies and team collaboration, and it will trace shifting skill requirements to produce clearer maps of emerging role families and career pathways. Results will be translated into empirically grounded guidance, such as diagnostic tools, practical recommendations and capability frameworks. These will be developed in collaboration with employers, unions and public bodies. Training brings together advanced empirical methods, human-centred design, socio-technical analysis and intersectoral secondments, all supported by a shared measurement strategy and transparent research practices. Through comparative studies, multi-level instruments and longitudinal data, the network will generate governance models, workflow insights, indicators of team interaction, and evidence on career development that can be applied across sectors. EMANAIRE aligns with European priorities on trustworthy, human-centred AI and contributes to the UN SDGs on decent work and industry, graduating researchers for trustworthy, inclusive and sustainable augmentation.