Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with a 5-year survival rate of approximately 18%. Early detection of HCC is crucial for treatment selection and improved patient survival. Conventional screening methods have limitations due to their inherent deficiencies and individual variability. Artificial intelligence (AI) is helping to increase the early detection rate of HCC by replacing manual tasks and uncovering hidden information in routine clinical data. Challenges such as ethical concerns, model instability, and generalizability issues must be overcome before AI can be fully implemented clinically. The article describes recent studies on AI models for early diagnosis of HCC, focuses on their applications and challenges. The aim is to critically assess the potential of AI to improve the early detection of HCC and the prognosis of patients.