Most organizations are experimenting with AI. Very few are building systems that can scale and produce true ROI for businesses.

In this session, Samantha St-Louis draws from real enterprise work to explore what it actually takes to move from disconnected AI experiments to cohesive, enterprise-ready agentic platforms that drive business revenue. We’ll examine how agentic systems behave at scale, where most organizations lose control, and why architecture and standards matter before velocity.

Attendees will learn how to design AI systems that coordinate multiple agents, preserve shared context, prevent duplication, and align technical decisions with long-term business outcomes. This is not a tool demo or a theoretical overview but a practical look at how modern organizations should be thinking about agentic AI as a platform, not a feature.

Ideal for leaders and architects who want to scale AI responsibly without slowing innovation... or waking up to AI sprawl six months from now.

Audience: Executives, enterprise architects, senior engineers, AI platform leaders

Level: Advanced / Strategic

Format: 45–60 min keynote or technical strategy session

Takeaway: Clear architectural principles for scaling agentic AI across an organization