Understanding human needs and the ways that workplace design can effectively address these needs is fundamental for improving the productivity and sustainability of a workforce. As automation increasingly replaces manual tasks in advanced manufacturing, it is crucial that human factors are considered throughout the stages of design and implementation. Initiatives like the EU AI-PRISM project aim to integrate human-centred design into new AI-based automation solutions to foster effective collaboration between humans and robots in challenging automated environments. AI-PRISM seeks to enhance productivity by combining advanced technology with human skills. To ensure that these automated solutions also meet the needs of their human operators and adhere to ethical standards, it is essential to incorporate human-centred design throughout both the design and implementation phases. The study described in this paper aims to identify the task-related challenges faced by current operators—from novices to experts—in four of the project’s use cases in manufacturing companies. To achieve this, four participatory design workshops were conducted to gather valuable feedback on the planned AI-PRISM automation solutions and capture operator requirements across different manufacturing sectors: wooden furniture, photonics and microelectronics, white goods and brewery. The workshops incorporated group interviews, lasting about one hour each, that provided a platform for operators to share their experiences, concerns, and suggestions regarding the integration of AI and robotics into their daily tasks. The results revealed that operators across all groups faced challenges with fault detection, precision, and repetitive tasks. Responses also included a number of recommendations for the design of AI-based automation to address these challenges including enhanced interaction interfaces, human oversight for precision tasks and robotic assistance. In conclusion, the findings from this research highlight the importance of aligning human skills with automated technologies, which can lead to a more efficient and effective future for manufacturing.