Serum protein electrophoresis (SPEP) is a valuable laboratory test that separates proteins from the blood based on their electrical charge and size. The test can detect and analyze various protein abnormalities, and the interpretation of graphic SPEP features plays a crucial role in the diagnosis and monitoring of conditions, such as myeloma. Furthermore, the advancement of artificial intelligence (AI) technology presents an opportunity to enhance the organization and optimization of analytical procedures by streamlining the process and reducing the potential for human error in SPEP analysis, thereby making the process more efficient and reliable. For instance, AI can assist in the identification of protein peaks, the calculation of their relative proportions, and the detection of abnormalities or inconsistencies. This review explores the characteristics and limitations of AI in SPEP, and the role of standardization in improving its clinical utility. It also offers guidance on the rational ordering and interpreting of SPEP results in conjunction with AI. Such integration can effectively reduce the time and resources required for manual analysis while improving the accuracy and consistency of the results.