The question, "How can AI-integrated BI curb healthcare fraud in emerging economies while simultaneously upskilling the workforce in data protection and real-time surveillance?", is a sophisticated inquiry that identifies both a pressing problem and a potential solution with a significant secondary benefit. The core issue is the widespread and often difficult-to-detect healthcare fraud that plagues many emerging economies due to reliance on manual processes and limited regulatory oversight. To combat this, the question proposes leveraging AI-integrated Business Intelligence (BI), which uses advanced machine learning to analyze massive datasets of healthcare claims and provider behaviors, proactively identifying and flagging fraudulent patterns that human auditors would likely miss. This technological solution, however, has an additional, transformative effect. By its very nature, the implementation and management of such a system requires training local professionals, which naturally addresses the existing skill gaps. As the workforce learns to operate these sophisticated tools, they gain invaluable, hands-on expertise in critical areas like secure data handling, ethical data management, and the practical application of real-time digital surveillance, thereby building a more competent and digitally-literate workforce for the future.