AI and the Evolution of Work: Redefining Project Management across Disciplines

Dear Colleagues,

The popularization of Large Language Models triggers a historic productivity boost across industries, professions, and workplaces. This boost is arguably comparable in magnitude to the introduction of the PC in 1981 into the workplace, but is more sudden as here, the speed of change is not limited by adoption rates of the PC. So far, productivity changes have been measured primarily at individual worker level in software engineering practice, and the consulting profession. However, as these new AI capabilities integrate further in other workplaces, how do specific disciplines other than software engineering change? How will traditional project roles adapt? How will the architecture, copywriting and medical profession’s way of working evolve? Besides social effects in this Issue, we are interested in the following:

The overall focus is on how AI tools are redefining project management paradigms across disciplines. For example, in engineering, the traditional Engineering Design Process is refined. In software, it is the agile paradigms. In Design thinking, the Design thinking methods are considered, etc.

The scope will encompass not just the technicalities, but we are also interested in societal implications—how these tools alter roles, the mental health implications of AI-driven workflows, and the emergence of novel tools and methods.

The purpose is to provide readers with a comprehensive understanding of the current landscape, the challenges, the opportunities, and the possible future trajectories. Additionally, it aims to share insights from one discipline to another. For example, in architecture practice, as generative AI lowers the cost of prototyping through parametric design workflows, how can the traditional workflow adapt?

Notwithstanding, the rapid advancements in AI, there is a lack of focused literature that holistically addresses its implications outside software engineering. In addition, while individual papers have touched upon AI-driven tools or processes, a collective volume that explores the future implications beyond the individual worker level and looks at the group level is missing. This Issue aims to fill this gap, making it a future essential read for scholars of Management of Information Systems, social scientists and anyone concerned in engineering design. It will complement the existing literature by providing practical insights and foresights based on real-world applications and academic investigations.

Dr. Jose Berengueres
Guest Editor

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• generalized AI Tools
• engineering design process
• software engineering
• MIS
• AI-driven workflows
• mental health implications
• AI in engineering education
• future of work