Abstract
This study frames AI into five successive generational AI All development phases of increasing complex program and platform diversity, whilst drawing on involving increasingly diverse and rich ‘global’ sources of ‘relevant’ data. It considers the AI techniques Rio Tinto applies at each generational level. It recognizes the AI complexities of resourcing, technologies, connectivities integrations, intelligent devices, and data-recall capacities on leading-edge firms and their ongoing competitiveness. It proposes a leading-edge firm timeline stagewise strategic AI feedback model.
Recommended Citation
Hamilton, John R. and Maxwell, Stephen J., "Artificial intelligence (AI), Rio Tinto and firm leading-edge ai competitiveness" (2023). ICEB 2023 Proceedings (Chiayi, Taiwan). 4.
https://aisel.aisnet.org/iceb2023/4