Liver cancer is one of the most challenging malignancies, often associated with poor prognosis and limited treatment options. Recent advancements in nanotechnology and artificial intelligence (AI) have opened new frontiers in the fight against this disease. Nanotechnology enables precise, targeted drug delivery, enhancing the efficacy of therapeutics while minimizing off-target effects. Simultaneously, AI contributes to improved diagnostic accuracy, predictive modeling, and the development of personalized treatment strategies. This review explores the convergence of nanotechnology and AI in liver cancer treatment, evaluating current progress, identifying existing research gaps, and discussing future directions. We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring of treatment efficacy, and enhance clinical decision-making. By integrating AI with nanotechnology, clinicians can achieve more accurate patient stratification and treatment personalization, ultimately improving patient outcomes. This convergence holds significant promise for transforming liver cancer therapy into a more precise, individualized, and efficient process. However, data privacy, regulatory hurdles, and the need for large-scale clinical validation remain. Addressing these issues will be essential to fully realizing the potential of these technologies in oncology.