Decision agents drive autonomy in AI systems. They combine generative AI or large language models for interaction and explanation, with machine learning for precision, and use decision models and business rules to act as a reliability layer. They allow each technology to play the role its best suited for. And, by focusing on the business decision being made rather than the specific technology being used, they keep business owners engaged.

This session will use real-world examples in banking, healthcare and insurance to illustrate the power of decision agents to personalize interactions, operationalize machine learning and augment human decision-makers. It will highlight how decision agents maximize the power of each technology, outline a proven development approach for decision agents, and share some dos and don’ts based on years of experience in developing autonomous systems.