Artificial intelligence (AI) and data analytics are critical tools for enhancing financial inclusion in developing economies. Financial inclusion, defined as the access and usage of financial services by all individuals and businesses, is essential for economic development and poverty reduction. However, many people in developing economies remain excluded from formal financial systems due to limited access to banking services, low financial literacy, and inadequate infrastructure. AI and data analytics offer innovative solutions to these challenges by enabling more accurate risk assessment, personalized financial guidance, and the development of alternative credit scoring models. AI technologies such as machine learning and natural language processing allow for the analysis of vast datasets to identify patterns, behaviors, and creditworthiness, facilitating better decision-making by financial institutions. AI-powered chatbots and virtual assistants provide personalized financial support, improving accessibility for marginalized populations. Data analytics helps financial institutions understand customer preferences and spending habits, enabling the development of tailored financial products and services. Additionally, data analytics supports the creation of alternative credit scoring models using non-traditional data sources, allowing individuals with limited credit histories to access credit on favorable terms. Despite these benefits, challenges such as data privacy, algorithmic bias, and the digital divide must be addressed to ensure equitable access to technology-enabled financial services. Successful initiatives like M-PESA, JUMO, and Tala demonstrate the transformative potential of AI and data analytics in expanding financial access and promoting economic empowerment. Future efforts should focus on research, policy development, and collaboration among stakeholders to build inclusive financial systems that empower individuals and communities. By leveraging AI and data analytics responsibly, developing economies can achieve greater financial inclusion and foster sustainable economic growth.Artificial intelligence (AI) and data analytics are critical tools for enhancing financial inclusion in developing economies. Financial inclusion, defined as the access and usage of financial services by all individuals and businesses, is essential for economic development and poverty reduction. However, many people in developing economies remain excluded from formal financial systems due to limited access to banking services, low financial literacy, and inadequate infrastructure. AI and data analytics offer innovative solutions to these challenges by enabling more accurate risk assessment, personalized financial guidance, and the development of alternative credit scoring models. AI technologies such as machine learning and natural language processing allow for the analysis of vast datasets to identify patterns, behaviors, and creditworthiness, facilitating better decision-making by financial institutions. AI-powered chatbots and virtual assistants provide personalized financial support, improving accessibility for marginalized populations. Data analytics helps financial institutions understand customer preferences and spending habits, enabling the development of tailored financial products and services. Additionally, data analytics supports the creation of alternative credit scoring models using non-traditional data sources, allowing individuals with limited credit histories to access credit on favorable terms. Despite these benefits, challenges such as data privacy, algorithmic bias, and the digital divide must be addressed to ensure equitable access to technology-enabled financial services. Successful initiatives like M-PESA, JUMO, and Tala demonstrate the transformative potential of AI and data analytics in expanding financial access and promoting economic empowerment. Future efforts should focus on research, policy development, and collaboration among stakeholders to build inclusive financial systems that empower individuals and communities. By leveraging AI and data analytics responsibly, developing economies can achieve greater financial inclusion and foster sustainable economic growth.