Machine learning is revolutionizing HIV treatment by predicting viral load suppression and optimizing antiretroviral therapy (ART). Researchers in Guinea have used AI models like Random Forest and Naïve Bayes to analyze patient data, achieving a 94% prediction accuracy. These insights help doctors personalize treatments, prevent drug resistance, and improve adherence strategies, particularly in low-resource settings. By integrating AI-driven predictions, healthcare providers can enhance HIV management and move closer to an HIV-free future.