The purpose of this review is to establish the role that AI and ML play in managing asthma and Chronic Obstructive Pulmonary Disease (COPD), with particular emphasis on disease management across various stages, diagnosis, and treatment personalization through monitoring. Data extraction was performed from articles published between December 2018 and October 2024, accessed using Scopus, PubMed, and Google Scholar databases. Articles focusing on the use of AI/ML in the management of respiratory diseases in clinical settings and real-life contexts were included in this study. Theoretical models or reviews of non-respiratory applications of AI/ML were excluded. AI and ML-based technology advancements provide the possibility to extend asthma and COPD management with many improvements. Such technologies can enable early and accurate detection by using advanced imaging and data analysis techniques. AI-driven models, such as MLMP-COPD, far outweigh the usual approaches made for predicting death and exacerbations. Big data analytics and telemedicine help in the integration of diverse data sources. AI and ML have an entirely new dimension and could perform more effectively for the management of both asthma and COPD. Practical implications include integrating AI-driven tools in clinical settings to improve diagnostic accuracy, enhance treatment, and assist in remote patient monitoring.