AI applications have proliferated, garnering significant intrest among information system scholars. AI-powered analytics, promising effective and low-cost decision augmentation, has become a ubiquitous aspect of contemporary organisations. Unlike traditional decision support systems (DSS) designed to support decision makers with fixed decision rules and models that often generate stable outcomes and rely on human agentic primacy. AI systems learn, adapt, and act autonomously, demanding recognition of IS agency within AI-augmented descision making ( AIADM) systems. This session will cover theory and practice with a set of actionable design principles to guide AIADM system design and development for product owners.