The aim of the paper is to contribute to the literature on the conceptualization of technology as an operant resource and the role of Artificial Intelligence (AI) in value co-creation processes. Resource integration and interaction determine such cocreation, however the issue pivots on whether AI is effectively able to co-create value as an operant resource. With an integrated framework based on the Service Science (SS), the Viable Systems Approach (VSA) & the Variety Information Model (VIM), the Authors show how to the various kinds of AI technology corresponds a diverse level of co-creation. Our (conceptual) study, highlights how AI (e.g. chatbot) with its client profiling capacity achieves consonance in a luxury goods context, thus interpreting customer expectations. At the same time, the man-machine virtuous circuit qualifies the shift from AI (a combination of various technologies with cognitive abilities-listening, comprehending, acting, learning and at times speaking-capable of matching human intelligence) to the more potent IA Intelligence Augmentation.

The main purpose of this contribution is twofold: from a scientific point of view, to interpret the symbiotic logic through the framework of the Viable Systems approach (vSa), and from a managerial viewpoint, to provide the actors of industrial symbiosis initiatives, at any stage of their life cycle, with a guide to the most promising web-based solutions in terms of defining the best configuration for the symbiotic network. The article, therefore, aims to provide an in-depth study of the existing literature, which is still not exhaustive, and to consider synoptically and comparatively the modern platforms capable of supporting industrial symbiosis initiatives. The objective was pursued by examining 10 existing and functioning Web-based platforms, of which only a few were previously explored in the previous literature, while the recognition of the latter was carried out on a bibliometric basis to articulate in more detail the existing gap based on a panel of contributions as large as possible. The joint consideration of the literature review and the examination of the existing and functioning platforms shows an articulated framework of approaches, proposed models, and classification schemes of their functions, which allows us to conclude that given the sectoral, territorial, and specific characteristics of the materials addressed by each platform and considering the different cycles existing in eco-industrial parks (water, energy, by-products, etc.), the most promising way for their implementation is to consider multiple platforms to fully exploit the contribution of each of them. As for the management implications, the suggestion is to integrate the results obtained from the different platforms and to evaluate the configurational alternatives with multi-criteria procedures.

The paper explores the interpretative significance of relevance in the systemic qualification of “intelligence,” particularly in the context of Intelligence Augmentation (IA). Using the Viable System Approach (VSA) matrix, it delves into Informational Variety and Systemic Relevance to understand the incremental impact of AI in complex decision-making. The study reveals that, methodologically, the relevance of the viable system explains the synergistic collaboration between humans and machines, considering technology not just as an influential resource but also possessing structural criticality. “Intelligent” service systems, based on AI, transform into “wise” systems when components cooperate with technological resources. This interaction, rather than amplifying human capabilities, leads to cognitive enhancement, streamlining decision-making. The abstract emphasizes the incompleteness of current support systems, which focus solely on the quantitative aspect of information, suggesting that greater efficiency necessitates integrating human experiences, knowledge, and emotions. It underscores that the role of technology lies in how humans interact with it, and as technology becomes increasingly critical, algorithms will progressively shape AI decision-making processes. In summary, AI facilitates the transition of the business system from an intelligent to a wise configuration, integrating the rational component of AI with the emotional aspect of human intelligence.