<p>With the rapid advancements in biomedical engineering, bioprinting has emerged as a pivotal solution to address the shortage of organ transplants and advance disease model research. The evolution of bioprinting has progressed from the fabrication of simple models (1.0) to the fabrication of permanent implants (2.0), tissue engineering scaffolds (3.0), and complex biostructures utilizing living cells (4.0). Nevertheless, significant challenges remain, particularly in accurately replicating the structure and function of host tissues, selecting appropriate materials, and optimizing printing parameters. The integration of artificial intelligence (AI), especially machine learning, provides promising novel opportunities in bioprinting (5.0). This review systematically summarizes the current applications of AI in bioprinting, discussing both construction strategies and application scenarios. It also explores the potential of AI to improve bioprinting in the preparation of complex functional tissues and in situ tissue repair. Overall, the synergy between AI and bioprinting is poised to drive the development of personalized medicine, facilitate high-throughput preparation of in vitro models, and provide robust tools for regenerative medicine and precision healthcare.</p>