The Integration of Artificial Intelligence with Microfinance Banking: Assessing Impacts on Financial Growth, Operational Efficiency, and Long-Term Sustainability

Abstract

The research examines how Artificial Intelligence operates within Microfinance Institutions to measure its influence upon financial expansion and process optimization as well as long-term organizational success. AI technology has achieved broad implementation in regular banking operations but its functions within developing economy microfinance structures continue to lack investigation. A quantitative study design uses structured surveys distributed to 300 participants made up of MFI staff and clients who were chosen through stratified sampling in both urban and rural regions. Extraneous data from institutional financial performance reports together with the main dataset helps to extend the analysis. The integration of AI produces substantial benefits for financial performance based on statistical analysis of regression tests and it enhances operational workflows while sustaining institution sustainability. Business entities implemented important AI services such as automated credit scoring and chatbots together with fraud detection systems which brought both operational advantages and cost reductions. The research output confirmed that sustained AI integration establishes a direct link with better operational performance and institution survival. The research endorses a framework for Artificial Intelligence deployment at Microfinance Institutions that should include responsible decision models which adapt to particular situations as well as training staff about digital skills and managing data effectively alongside intelligent machine-assisted human interaction systems. This research demonstrates the necessity to solve both structure-based and moral complications within technological deployment. Studies should use multi-stage research designs across multiple nation states to study how AI technology affects microfinance banking systems in both short-term and long-term time periods.