In this paper, my coauthors and I examine how organizations can design more human-centred systems as AI becomes embedded in core management functions such as hiring, training, performance evaluation, and compensation. We show that the key design question is when AI should automate work, when humans and AI should share decisions, and when human involvement remains essential. This depends not only on how routine or cognitively complex a task is, but also on whether people see AI’s role as acceptable and fair—especially in high-stakes decisions that affect careers and livelihoods. The paper highlights why explainability, fairness, and professional identity matter so much: even a technically effective system may fail if employees do not understand it, trust it, or feel it strips away meaningful human judgment. The broader message is that designing human-centred organizations in the age of AI means building systems that improve efficiency without losing fairness, accountability, and the vital role of human professionals in shaping important decisions.

In this paper, I explore what it would mean to build organizations for a world where social interaction increasingly takes place in immersive virtual environments rather than only in physical offices or on flat screens. My coauthor and I argue that the metaverse is not just a new technology platform, but a new organizational setting that could reshape how people collaborate, learn, and express social roles through digital representations such as avatars. The key question is not whether virtual worlds will perfectly replace face-to-face interaction, but how organizations can use them to support richer, more spontaneous, and more engaging forms of connection than typical remote-work tools allow. At the same time, these environments will only become valuable if managers understand how human relationships, identity, and collaboration change when interaction is mediated through persistent virtual spaces. The broader message is that designing human-centred organizations for the future means thinking seriously about which forms of connection, trust, and collective work can be re-created in new digital environments.

In this paper, I explore how work itself may need to be redesigned as people increasingly collaborate through multiple AI agents acting on their behalf. I propose a new model in which each person leads a small “team” of AI representatives with different roles, levels of authority, and degrees of closeness to the human’s current goals and preferences. I show how this could reduce coordination overload, speed up routine decisions, and make collaboration more adaptive—for example by letting AI agents prepare options, handle low-risk handoffs, or negotiate across teams before humans step in at the moments that really require judgment, trust, and accountability. At the same time, I emphasize that this kind of workflow redesign only works if organizations put strong safeguards in place so people know when they are interacting with AI, humans remain responsible for important decisions, and technology strengthens rather than erodes human connection. In short, this research asks how we can redesign workflows around distinctly human strengths—judgment, meaning-making, and relationship-building—while letting AI take on more of the coordination burden.