Several prior studies emphasised artificial intelligence’s (AI) massive potential in making education more accessible. However, the open and distance learning (ODL) environment has not fully realised the expectations of AI. The heart of the challenge lies not in recognising AI’s potential but in harnessing its capabilities effectively within dynamic educational environments. This current study investigates the transformative impact of AI in ODL. The critical need to understand how AI influences learner outcomes in ODL environments was addressed. A process-based framework and research model tailored for AI applications in ODL were developed in this research paper. The study utilised diverse elements comprising AI adoption drivers, its ensuing consequences on academic achievements, the predictive capabilities of machine learning, and inherent gender and regional disparities. Our findings demonstrate the framework’s adaptability across various AI algorithms, offering significant implications for enhancing learner’s experiences in ODL. The research community would benefit significantly from the developed framework and research model by integrating machine learning algorithms such as support vector machines (SVM). This integration, slated for future endeavours, promises to enhance the predictive efficacy and adaptability of the framework in real-world ODL scenarios.