ARTIFICIAL INTELLIGENCECE (AI) –DRIVEN HEALTH MESSAGING AND SUPPORT SYSTEM ON EXLUSIVE BREASTFEEDING PRACTICE AMONG NURSING MOTHERS IN AKOKO-EDO, LOCAL GOVERNMENT AREA OF EDO STATE

This investigation sought to determine the influence of an Artificial Intelligence (AI) support system on the uptake of Exclusive Breastfeeding (EBF) practices among 189 nursing mothers within the Akoko-Edo Local Government Area of Edo State. A quasi-experimental design was utilized, wherein participants were surveyed and allocated to either a control group or an intervention group receiving individualized, AI-powered EBF counseling (e.g., chatbot or tailored SMS). Baseline analysis indicated a disparity between good maternal EBF knowledge and suboptimal practice levels. Key impediments were identified as deeply rooted cultural and religious convictions, maternal health challenges, and environmental constraints like the lack of convenient, private breastfeeding areas. The target population were selected nursing mothers of Akoko-Edo local Government Edo State. The sampling technique that was used in this study is simple random sampling techniques; every member of the target population has an equal chance of being selected. 196 Respondents was used for the study. The mother was selected randomly, administering questionnaire to them to get the data for the study. A self-developed structured questionnaire was used to gather information on the research topic. The data for this study was collected by the researcher with the aid of a self-developed questionnaire method. The questionnaires were distributed to the nursing mothers in the study area. Efforts were made to acquaint them with the overall focus of the study and the need to give accurate information on the questions stated in the questionnaire. The data collected for this study was analyzed with the use of Statistical Package for Social Science (SPSS) version 21. The results were presented using frequency counts, percentage distribution, mean and standard deviation. The implementation of the AI system resulted in a significant positive change in EBF compliance for the intervention group. The result from the study reveals that majority have good knowledge of breastfeeding were between ages 21-30years, the highest percentage 65.4% of the respondents were married 48.7% had secondary education, 37.2% of mothers were Employed, Majority 60.2% were Yoruba, the highest percentage 72.8% had monogamous family setting and 27.2% polygamous family setting. We conclude that while EBF knowledge is a necessary precondition, the strategic use of accessible AI technology offers a powerful mechanism to bypass traditional practice barriers and dramatically improve universal EBF adoption. Future policy should merge supportive workplace guidelines with AI-driven assistance to facilitate continued compliance.