The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland

Abstract

The world’s current linear economic model is unsustainable. This model encourages improper use of limited natural resources and causes abundant waste production resulting in severe harm to the environment. A circular economy (CE) is a sustainable, restorative, and regenerative alternative to the current linear economy and is gaining popularity worldwide. Amongst various digital technologies, Artificial intelligence (AI) is a crucial enabler for CE and can aid significantly with the adoption and implementation of CE in real-world applications. In this paper, we describe the intersection of AI and CE and policies around implementing CE principles using AI. As a means of grounding the discussion, we discuss some initiatives taken by the Irish government to adopt circularity and explore the role AI plays in these. We present a number of practical examples of AI and CE from Ireland. We argue that digitalisation has potential in CE and it has a major role to play in the transition towards CE. We close the paper by reflecting on future steps around practical implementations of AI-based CE processes.

Driving Circular Economy through Digital Technologies: Current Research Status and Future Directions

“…Blockchains are widely used in the field of business economics for intra-enterprise collaboration, crossborder payments, transaction security, and data transparency to help organizations establish transparent, secure, and reliable transaction environments, reduce time and resource costs, and improve trust [49,56]. The integration of AI and big data analytics can be used to understand customer needs, manage customer relationships, and make personalized recommendations by predicting trends, and improving customer satisfaction and fraud prevention [16,32].…”

“…The "blue" cluster is associated with "products", and "business models" and the "yellow" cluster is mainly related to DTs. monitored and exchanged for decision making [32,63]. As such, these intelligent decisionsupport systems improve the competitiveness of organizations.…”

“…Digital twins are currently mostly used in the aerospace and automotive industries, to simulate performance [29], and are also used in the field of the built environment to A CE in "Operations Research Management Science" could help with resource management, including the management of waste materials, backlog inventory, and human resources, and improve the flexibility and sustainability of the supply chain. By using machine learning and AI, organizations make smarter decisions, including resource allocation, product design, and market positioning, via cyber-physical systems that connect cyberspace, physical processes, and objects, from which real-time data can be monitored and exchanged for decision making [32,63]. As such, these intelligent decision-support systems improve the competitiveness of organizations.…”

“…AI is considered as a technology with great potential to drive CE development, identifying new routes for CE development and improving the quality of processes, including data analytics, predictive analytics, reverse logistics, improved process optimization, and enhanced responsiveness in the transition to a regenerative economic model. In addition, how the AI can positively impact the transition to CE, describing the practical applications of AI in the CE, through examples, has been explored [32], such as iteratively assisted design processes and predictive maintenance to keep products, components and materials at their optimum value, reduce equipment costs, and extend service life [92,93]. Further, the findings reveal that AI could enhance the necessary infrastructure elements in the production phase as well as in the recycling phase, resulting in sustainable ways to optimize resource use to promote circular businesses and practices [50].…”

“…The results shown in Figures 3 and 4 suggest that adding more literature does not make a significant difference to the study of the current research status and overall development trend of "CE" and "DTs", but more clearly indicates the co-occurrence effect with keywords. In general, DTs include big data [28], the internet of things [29], digital twins [30], blockchains [31], artificial intelligence [32], additive manufacturing [33], 3D printing [34], BIM [35], cyber-physical systems [36], cloud computing [37], virtual reality [38], augmented reality [39], mixed reality [39], and robotics [37]. During the data screening, the DT keywords associated with the CE were used, resulting in studies more related to Industry 4.0 and the CE.…”