Artificial Intelligence and the Metaverse for Collaboration in High-Risk Environments: A Socio-Technical Analysis

Collaboration in organizations is no longer merely enabled by technology; it is increasingly constituted through it. Technology-mediated workflows now serve as the coordinating infrastructure for collective work, integrating globally dispersed teams, shortening innovation cycles, and aligning diverse expertise productively. This trend continues a long historical development in which successive waves of technology have expanded the circle of those who can collaborate, what can be shared, and when and where collaborative work can take place. The shift to remote and hybrid work has made these developments explicit, as tasks like recruitment, training, and routine coordination increasingly occur through technology-mediated channels. These gains in reach and pace were accompanied by persistent drawbacks—reduced social presence, weaker nonverbal signaling, and more fragile trust—the very conditions under which meaning is negotiated and role expectations are established. In ordinary settings, these gaps mainly lower efficiency, but in high-risk environments marked by tight coupling and complex interactions, slight deviations can cascade into systemic failures. Consequently, the question is not how to add more tools for incremental improvements in existing systems, but how to deepen collaboration—how to restore missing cues, align attention in real time, and build a shared frame for inference and action. In this regard, two developments stand out. First, artificial intelligence (AI) is evolving from a passive tool to an active collaboration partner. Rather than automating narrow subtasks, AI is now taking on tasks long performed by human experts—such as predicting floods and forecasting utility outages—thereby augmenting human judgment when cognitive demands exceed human capacity and, in acute phases, temporarily substituting for it. This shift is forcing organizations to reassess the composition of their teams, the division of responsibilities, and the governance of decisions. In parallel, the metaverse emerges as a new collaboration environment. Users can meet as avatars in shared three-dimensional spaces that blend the richness of in-person interaction with the flexibility of digital communication, frequently enhancing motivation, active learning, and social presence beyond standard video calls. This seamless transition between virtual and real-world applications represents a fundamental advantage of metaverse-based collaboration, especially in high-risk environments: teams can rehearse realistic scenarios, co-construct knowledge, and move fluidly between training and practice. However, this also raises questions about data and dignity: how personal and biometric information is handled and how identity and anonymity are managed in the workplace. To guide researchers and practitioners in integrating AI and the metaverse in ways that enable—rather than displace—collaboration, this dissertation adopts a socio-technical perspective across three levels, progressing from organizational teams to organizational leadership to high-risk environments, where demands on collaboration are highest. Regarding the team perspective, this dissertation examines how emerging technologies can promote collaboration in organizational teams. One study investigates socio-technical design levers and summarizes research findings to distinguish four areas—environment, collaboration, avatars, and individual behavior—thereby elevating outcome measurement, design quality, and security as cross-cutting priorities. The synthesis indicates that engineered social presence reduces uncertainty and supports communication; well-designed contexts cultivate trust, knowledge transfer, and cohesion; and risks such as disruptive behavior and privacy concerns require explicit governance. A second study assesses willingness to adopt these tools and role-specific conditions using an online experiment in which leaders and members conduct a feedback conversation in a metaverse workspace. This study extends a technology-acceptance framework with social presence and privacy concerns, suggesting that maximizing perceived co-presence secures executive approval while mitigating privacy risks and reducing member resistance. A third study details how implementation mechanisms generate these conditions in everyday collaboration. Results of expert interviews suggest that sustainable AI practices can be established to strengthen collaboration and coordination when the right infrastructure, skills, and safeguards are in place. Together, these studies highlight that effective team collaboration with AI and in metaverse settings depends on purposeful design for social presence and coordination, robust privacy and security governance, equitable enablement, and rigorous evaluation of outcomes. From a leadership perspective, this dissertation examines how emerging technologies promote collaboration in organizational leadership. One study investigates how leaders’ personality traits influence the adoption of the metaverse for collaborative work, utilizing a scenario-based online experiment and structural equation modeling. The results show that conscientiousness and extraversion increase leaders’ intention to use the metaverse for collaborative tasks. At the same time, openness to experience boosts personal innovativeness, and neuroticism shows no reliable effects. In contrast, a second study specifies how collaboration can be instantiated through AI, following a design science process that derives design requirements and design principles for an AI leader from expert interviews, focus groups, and evaluations, with prototypes illustrating transparent communication, clarified roles, coordinated work, structured feedback, and sustained engagement when conversational capability, explainability, and human-in-the-loop controls are jointly designed. These findings underscore that effective collaboration in virtual teams emerges from the interplay of human dispositions and carefully designed AI, enabling credible co-leadership in digitally mediated work. To scale these benefits, a third study proposes a make-or-buy decision framework for AI services based on a case study in a mobility and logistics group, highlighting strategic importance and data security as primary factors, emphasizing case fit as an AI-specific discriminator, and staging classic considerations such as internal resources and costs. Regarding the high-risk-environment perspective, this dissertation investigates how emerging technologies can promote collaboration in high-risk environments. One study examines how xReality (XR) technologies can coordinate collaboration and learning across preparedness, response, and recovery, therefore aligning applications to technology readiness and the disaster management cycle. The results show a concentration of work in virtual reality (VR) prototypes, with fewer mature augmented reality (AR) and mixed reality (MR) deployments, suggesting that immersive systems can strengthen shared situational awareness, enable remote collaboration in joint virtual spaces, and support after-action learning—while frontline translation hinges on interoperability with incumbent systems and rigorous field evaluation. A second study derives actionable design knowledge for a metaverse platform in crisis management, guided by a kernel theory emphasizing agility, designation, alignment, participation, and trust. The results show that metaverse capabilities can verify information, synchronize distributed actors around a shared 3D operational picture, and bridge simulation and practice through recording, replay, and knowledge capture. Extending preparedness beyond professional responders, a third study co-designs a community preparedness platform using iterative design science. The results indicate that immersive simulations, gamified learning, and collaborative scenario exercises can narrow the awareness–action gap by operationalizing guidance and reducing barriers to execution. Collectively, the studies underscore that effective crisis collaboration in the metaverse and across XR hinges on the strategic alignment of organizational maturity, experience design, and inclusive participation to sustain resilient operations under uncertainty. The studies presented in this dissertation highlight that collaboration is no longer merely enabled by technology but actively co-constructed with it—across teams, leadership, and high-risk environments. They demonstrate that engineered social presence, clear decision rights, and human-in-the-loop oversight can strengthen coordination, broaden knowledge sharing, and preserve expert judgment—but only when design and governance are deliberate. Without such discipline, socio-technical systems can instead magnify privacy risks, distort signals, and erode trust, particularly in tightly coupled, high-risk contexts. This dissertation contributes to the growing understanding of emerging technology—especially AI and the metaverse’s role in collaboration by offering practical strategies for designing, integrating, and governing collaboration partners and environments that augment rather than displace human capability. In doing so, it provides a foundation for research on collaborative norms, evaluation metrics, and implementation pathways that sustain co-presence and enable co-creation—without compromising human agency in collaboration.