Responsible or Sustainable AI? Circular Economy Models in Smart Cities

Abstract

Responsible artificial intelligence (RAI) has been increasingly embedded within circular economy (CE) models to facilitate sustainable artificial intelligence (SAI) and to enable data-driven transitions in smart-city contexts. Despite this progression, limited synthesis has been undertaken to connect RAI and SAI principles with their translation into policy, particularly within deep learning contexts. Accordingly, this study was designed to integrate RAI and SAI research within CE-oriented smart-city models. A science-mapping and knowledge-translation design was employed, with data retrieved from the Scopus database in accordance with the PRISMA 2020 flow protocol. From an initial yield of 3842 records, 1176 studies published between 1 January 2020 and 20 November 2025 were included for analysis. The first set of results indicated that publication trends in RAI and SAI for CE models within smart-city frameworks were found to be statistically significant ((Formula presented.) = 0.94, p < 0.001). The second set of results revealed that circular manufacturing, waste management automation, predictive energy optimisation, urban data platforms, and smart mobility systems were increasingly embedded within RAI and SAI applications for CE models in smart-city contexts. The third set of results demonstrated that RAI and SAI within CE models were found to yield a significant effect (M = −0.61, SD = 0.09, t(9) = 7.42, p < 0.001) and to correlate positively with policy alignment (r = 0.34, p = 0.042) in smart-city contexts. It was therefore concluded that policy-responsive AI governance is required to ensure inclusive and sustainable smart-city transformation within frameworks of RAI.