The Role of Artificial Intelligence in Enhancing Infection Control in Hospitals: A Systematic Review

Hospital-acquired infections represent a critical global healthcare challenge, affecting 7–10% of hospitalized patients worldwide with 1.4 million annual deaths. This systematic review examines the transformative potential of artificial intelligence in infection control through predictive analytics, real-time surveillance, and antimicrobial stewardship. Analyzing 50 peer-reviewed studies, we demonstrate the effectiveness of AI tools in reducing infection rates by 35% and improving antibiotic utilization by 90%. We identify key implementation barriers, including data integration challenges, algorithmic bias, and ethical concerns. By synthesizing real-world case studies and proposing a three-phase implementation model, this review bridges the gap between technological capabilities and hospital infection control policies, offering practical recommendations and outlining a roadmap for future integration.