The study titled "GPT-4-based AI agents-the new expert system for detection of antimicrobial resistance mechanisms?" is critically important as it explores the integration of advanced artificial intelligence (AI) technologies, like generative pre-trained transformer (GPT)-4, into the field of laboratory medicine, specifically in the diagnostics of antimicrobial resistance (AMR). With the growing challenge of AMR, there is a pressing need for innovative solutions that can enhance diagnostic accuracy and efficiency. This research assesses the capability of AI to support the existing two-step confirmatory process recommended by the European Committee on Antimicrobial Susceptibility Testing for detecting beta-lactamases in Gram-negative bacteria. By potentially speeding up and improving the precision of initial screenings, AI could reduce the time to appropriate treatment interventions. Furthermore, this study is vital for validating the reliability and safety of AI tools in clinical settings, ensuring they meet stringent regulatory standards before they can be broadly implemented. This could herald a significant shift in how laboratory diagnostics are performed, ultimately leading to better patient outcomes.