The service sector dominates the economy, with services – encompassing everything from healthcare and education to finance, entertainment, hospitality, transportation, government, information technology and much more – now making up most GDP and employment globally (OECD, 2017; World Bank, 2023). In this context, our understanding of economic exchange has shifted from focusing on the production of tangible output to focusing on value co-creation within business and social systems. On this view, value is not something embedded in a product at a factory; rather, value is co-created when skills and knowledge are applied for mutual benefit at the time of and in the context of use (Vargo Miles, 2010; see also Barrett, Davidson, Prabhu, it must alter the institutional arrangements that determine how value is assessed and exchanged. Thus, innovation requires institutional work in which actors break existing rules, make new rules and maintain these new structures until they become the accepted standard (Koskela-Huotari et al., 2016). Central to this institutional view is the reconfiguration of roles and relationships within a service ecosystem. For example, in the healthcare service system, the shift from provider-centered to patient-centered care represents a service innovation that was not primarily a technological change but a relational one: the patient's role shifts from passive recipient of treatment to active partner in wellness and the physician's role shifts from authoritative prescriber to collaborative partner, changing the institutional norms and establishing new practices for information sharing (Patrício et al., 2020). Similarly, the sharing economy platform Airbnb did not create new housing stock; it reconfigured the role of the homeowner from private resident to service provider and established new institutional rules (trust mechanisms) to govern relationships between strangers (Lusch Normann, 2001; Vargo, Fehrer, Wieland, collecting data generated by these connected sensors; computing and processing data, identifying patterns and generating predictions (such as forecasting traffic congestion); communicating insights back to system participants, informing them of optimal choices; co-creating value by using this information to help integrate resources and controlling the system to take autonomous action based on the data, optimizing operations in real-time (Lim Yee et al., 2025). This suggests that sustained competitive advantage lies in mastering complexity through augmenting human capabilities rather than optimizing routine transactions (see also Manyika, Johnson, see Spohrer, Maglio, Vargo, Spohrer, 2024), liquefying the individual's presence and expertise. The effectiveness of an augmented workforce depends on establishing robust frameworks for human-machine teamwork (Kunz, Sajtos, Mortati for instance, the potential of conscious AI or highly autonomous service robots may require new institutional structures to manage the rights of digital workers (Breidbach et al., 2025).
Paul P. Maglio (Tue,) studied this question.