Agentic AI

Agentic AI refers to a new paradigm in artificial intelligence where systems move beyond simple task execution to demonstrate autonomy and reasoning. An Agentic AI entity is designed to establish its own goals, generate a plan to achieve those goals, execute the necessary steps, monitor its progress, and autonomously adapt its plan based on feedback or unexpected outcomes. This contrasts with traditional AI, which typically requires precise, step-by-step human instructions for every action. In the life sciences, Agentic AI is poised to revolutionize complex workflows like drug discovery and supply chain management. For instance, an AI agent could be tasked with “finding the optimal therapeutic candidate for a specific protein target.” It would then autonomously run molecular simulations, interact with large datasets, design new compound structures using Generative AI, schedule lab automation protocols, and even proactively manage inventory for its experiments. The rise of agentic systems in 2025 signifies a major leap in AI’s value proposition, enabling a 10x increase in research productivity and dramatically accelerating the pace of innovation across the biopharmaceutical value chain. The focus is shifting from simply having powerful AI models to having AI entities that can act and manage themselves.