AI Leadership Insights: Agentic RAG

In this episode of the Techstrong AI Leadership Insights show, host Mike Vizard sits down with Patrick Jean, chief product and technology officer at ABBYY, to discuss advancements in Retrieval Augmented Generation (RAG) and the emerging concept of “agentic RAG.” Patrick explains that while traditional generative AI models produce text based on learned data, RAG models enhance this by retrieving real-time information, ensuring outputs are current without retraining. Agentic RAG takes this further by introducing autonomy, allowing systems to not only generate information but also perform actions and make decisions, approaching tasks with a level of hierarchical planning that resembles human thought processes.

The discussion also explores how trust and governance are essential for deploying autonomous AI agents effectively. Patrick emphasizes that, much like humans, AI systems need consistent behavior and transparent frameworks to establish reliability and trust. He highlights potential applications across industries, including self-driving cars, health care and home automation, where autonomous agents could enhance efficiency. However, P.J. notes the importance of establishing guardrails and guidelines, enabling AI systems to function safely while working collaboratively in a trust-based ecosystem.