Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review

This paper investigates the literary corpus on the role of Artificial Intelligence (AI) in the construction of sustainable business models (SBMs). It provides a quantitative overview of the academic literature that constitutes the field. The paper discusses the relationships between AI and rapid developments in machine learning and sustainable development (SD). Specifically, the aim is to understand whether this branch of computer science can influence production and consumption patterns to achieve sustainable resource management according to Sustainable Development Goals (SDGs) outlined in the UN 2030 Agenda. Moreover, the paper aims to highlight the role of Knowledge Management Systems (KMS) in the cultural drift toward the spread of AI for SBMs. Despite the importance of the topic, there is no comprehensive review of the AI and SBM literature in light of SDGs. Based on a database containing 73 publications in English with publication dates from 1990 to 2019, a bibliometric analysis is conducted. The findings show that the innovation challenge involves ethical, social, economic, and legal aspects. Thus, considering that the development potential of AI is linked to the UN 2030 Agenda for SD, especially to SDG#12, our results also outline the framework of the existing literature on AI and SDGs, especially SDG#12, including AI's association with the cultural drift (CD) in the SBMs. The paper highlights the key contributions, which are: i) a comprehensive review of the key underlying relationship between AI and SBMs, offering a holistic view as needed, ii) identifying a research gap regarding KMS through AI, and iii) the implications of AI concerning SDG#12. Academic and managerial implications are also discussed regarding KMS in the SBMs, where the AI can represent the vehicle to meet the SDGs allowing for the identification of the cultural change required by enterprises to achieve sustainable goals. Thus, business companies, academic research practitioners, and state policy should focus on the further development of the use of AI in SBMs.