Balancing Individual AI-Augmentation with Organisational Stability
Short description
Employees are building personalised AI workflows, sometimes outside formal organisational systems. This project studies how individual experimentation, personal digital infrastructures and “shadow AI” affect collaboration, oversight and organisational resilience. It compares bottom-up adoption with top-down rollout and follows consequences for trust, disclosure, handovers and continuity.
Longitudinal cases will combine observation, digital diaries and interviews with collaboration-network analysis. The research aims to explain the trade-offs between individual augmentation and collective stability, and to develop guidance on disclosure norms, versioning, audit trails and workflow portability that helps organisations retain the benefits of experimentation.
Interested in this project?
Applications are open at the University of Zurich. Apply by 10 October 2026. The intended start date is 1 January 2027.
View the UZH job advertisementSubmit through UZH’s official application procedure. The advertisement sets out the required documents and full employment terms.
You may apply to up to four EMANAIRE doctoral projects. Submit a separate application for each position and briefly identify your other EMANAIRE applications, including any you intend to submit, in each motivation or cover letter.
What the project involves
- Examine how employees build personalised AI workflows and how these affect collaboration, oversight and resilience.
- Compare individual experimentation with organisational rollout, tracing consequences for trust, disclosure and continuity.
- Combine longitudinal cases, observation, digital diaries and interviews with collaboration-network analysis.
- Develop guidance on disclosure, versioning, audit trails and workflow portability.