The accelerating digital transformation of healthcare systems has positioned artificial intelligence (AI) as a crucial tool for enhancing the efficiency and accuracy of medical services. This review examines the emerging applications of AI within biochemistry and microbiology, two fundamental laboratory disciplines vital to diagnosis and treatment. The core discussion centers on how AI is revolutionizing processes through data analysis, enabling predictive diagnosis, and automating workflows to significantly reduce human error. In biochemistry, the "clinlabomics" approach transforms routine tests into strategic data sources for early disease prediction and risk estimation, while in microbiology, AI accelerates pathogen detection and drives the discovery of new antimicrobial agents. Shared challenges, including data privacy and the need for explainable AI, are analyzed. Ultimately, the successful and sustainable integration of AI into these laboratories will fundamentally improve patient outcomes and reshape the future of clinical diagnostics.