<![CDATA[The integration of Artificial Intelligence (AI)-driven applications into economic data analysis is rapidly transforming how tertiary institutions approach research, forecasting, and policy planning. These tools offer enhanced precision, real-time analysis, and automation, enabling educators and researchers to interpret large-scale economic datasets with greater accuracy. This study used a descriptive survey design to explore how AI-driven applications influence economic data analysis among 106 lecturers in tertiary institutions across Anambra State, Nigeria. Participants were purposively selected based on their experience with AI tools. Data were collected electronically using a validated and reliable questionnaire, with a Cronbach Alpha value of 0.84. The instrument was reviewed by experts to ensure content validity. Data analysis involved descriptive statistics for answering research questions and ANOVA for testing hypotheses at a 0.05 significance level. The findings revealed that AI-driven applications significantly improved the efficiency of economic data analysis, with teaching experience being a key factor in their effectiveness. However, age and the interaction between age and experience did not have significant effects. The study highlighted the potential of AI applications for economic analysis but also pointed out the importance of institutional readiness and expertise in maximizing their benefits. Based on these results, the study recommended enhancing AI integration and providing targeted training to support data-driven decision-making in academic and policy contexts.]]>
