This study introduces a novel framework that integrates the Analytic Hierarchy Process (AHP) with advanced large language models (LLMs) to automate and enhance multi-criteria decision analysis (MCDA), particularly in cybersecurity applications. By leveraging the capabilities of these LLMs, we create a system of AI agents that effectively replace human input in the AHP process, from criteria selection and pairwise comparisons to alternative evaluation. This automation increases efficiency, ensures judgment consistency, and reduces potential biases. Our findings demonstrate the feasibility and transformative potential of this approach, showcasing its ability to generate reliable and consistent AHP results. This framework establishes a new paradigm for intelligent decision support systems by merging traditional MCDA methodologies with cutting-edge AI, opening promising avenues for future research and applications in various domains. Keywords: Analytic Hierarchy Process, multi-criteria decision analysis, Decision support systems, Large Language Models, AI agents, Cybersecurity