Artificial Intelligence for a Profitable Sustainable Transition: A Bibliometric Mapping of the Literature

Since the promulgation of sustainability development goals (SDGs) and Paris Agreement, different actors have been attempting the transition towards clean, sustainable future. Corporate firms are also reprioritising and reshaping operations to achieve sustainable outcomes without compromising on profitability. Recently, artificial intelligence (AI) has attracted attention of such organizations because of the efficiency and solutions it promises. AI is being deployed and integrated by organizations to achieve a balance between sustainability and profitability. These interactions and intersections are expected to reshape the corporate sector. While there is substantial literature on sustainability, the intersection between AI, sustainable transition and corporate monetisation strategies remains underexplored vis-a-vis how AI can contribute to profitability and achieving decarbonization and/or sustainability goals. This article reviews and maps the existing literature using bibliometric analysis. A keyword search strategy was developed and employed across a time horizon of the last 10 years. The results provided evidence of the key themes/sub-themes which still require further scholarly attention. The emerging clusters from the bibliometric analysis are also instructional as regards the areas where more focus might still be warranted. The chapter provides interpretation of the trends, data and cluster formation and utilises NRBV as an interpretative lens.