The present research is a review-based study with the objective to understand the Artificial Intelligence (AI) in enhancing the sustainability of microfinance lending by leveraging secondary data from industry reports, financial institutions, and academic research. AI-driven solutions, including machine learning algorithms, credit risk assessment models, and automated decision-making, have been increasingly adopted to improve efficiency, reduce default rates, and optimize resource allocation. The study further highlights the challenges of AI adoption, such as ethical concerns, data privacy issues, and technological infrastructural limitations. Ultimately, the integration of AI in microfinance lending presents a transformative opportunity for sustainable growth, improving financial accessibility while mitigating risks. Future research should explore regulatory frameworks and long-term impacts of AI-driven microfinance models.