This study investigates how the integration of business analytics with capital budgeting frameworks can improve decision-making for hospital techno-medical equipment procurement. As healthcare institutions face increasing financial constraints and a growing need for efficient resource allocation, analytical dashboards offer a structured approach to consolidating financial, operational, and supplier-based information. The research adopts both descriptive and analytical methods, utilizing primary data gathered through structured questionnaires administered to hospital stakeholders and secondary data sourced from institutional reports, procurement records, and published studies. Advanced analytical tools such as Principal Component Analysis (PCA) and Power BI-based visualization techniques were employed to identify critical decision factors and enhance interpretability.

The results show that data analytics and AI improve food tracking, maximize the use of resources, and support sustainability initiatives.  However, there are still issues, such as a lack of digital skills, risks to cybersecurity, and regulatory demands.  Financial and resource limitations particularly impact small and medium-sized businesses (SMEs).  The report suggests working with regulators, training employees, and conducting small-scale pilot testing of AI solutions.  Future studies should evaluate possibilities for AI to create sustainable food systems, particularly in developing countries, as well as long-term economic benefits and ethical issues.