Artificial intelligence as a driver of corporate sustainability metrics and triple bottom line engagement in supply chains

Despite global attention and increased investment, the implementation of digital technologies, for instance, artificial intelligence (AI), and its impact on sustainability metrics (SMII) and triple bottom line awareness (SEI) within large global supply chain companies, remains unclear. Digitization does not always promote sustainability due to high energy use and social inequality; ESG goals may also pose hurdles to further digital transformations. In contrast, long-term digitization is a driver of achieving sustainable goals. Due to a lack of consensus, this study researches the impact of implemented AI technology on SMII (operational level) and SEI (strategic level) within large, global supply chain firms. The study includes a literature review of 817 sources on the main theories and possible variable relationships. Secondary data from Fortune 500 industrial companies and their integrated, annual, and sustainability reports were collected and analyzed, yielding 10 digital technologies and 12 sustainability metrics as a basis for the subsequent survey of 106 participants. PLS-SEM modeling is used to test and interpret two hypotheses and to validate results. This study reveals a positive and significant relationship in implementing AI and a global supply chain company’s SEI. This is explained by Institutional theory - external pressures and competition, also, that the large international companies have greater resource availability per the Resource Orchestration theory. Further studies could examine why AI affects sustainability at the strategic level but has little impact on the operational level.