As AI adoption accelerates, organizations are pushing beyond basic Retrieval-Augmented Generation (RAG) systems to solve lingering challenges around accuracy, context awareness, and reliability. Agentic systems add reasoning, planning, and decision-making capabilities to traditional RAG pipelines, transforming them from passive lookup tools into active problem-solvers. The result? AI that’s not only more reliable, but also better at understanding context, asking the right questions, and guiding itself to better answers.
In this follow-up to our previous "Unlocking the Value of AI" session, we’ll explore how Agentic RAG works, why it represents an evolution in AI system design, and how it addresses the shortcomings of traditional RAG pipelines. You’ll walk away with a clearer understanding of how these new concepts can strengthen your AI initiatives and deliver more trustworthy results.
💡 You’ll Learn:
- What Agents are and how Agentic-RAG differs from traditional RAG / LLM approaches
- How agentic workflows improve reasoning, reduce hallucinations, and handle complex tasks
- Practical ways to assess if your current AI systems could benefit from an agent-based approach
- Key strategic considerations for integrating Agentic RAG into your AI roadmap
🧠 Who Should Attend?
- C-level executives and VPs exploring advanced AI strategies
- Product Leaders and Innovation Executives shaping AI capabilities
- Data and Analytics Leaders responsible for delivering trustworthy insights
- Teams already using RAG who want to push performance to the next level
- Anyone responsible for critical decision-making powered by AI
The conversation will be high-level and jargon-free, with plenty of time for Q&A.