Candice Quadros explains why enterprises need clear ownership, visibility, and governance designed for autonomous AI agents before adoption outpaces control.
About Candice Quadros
Candice Quadros is an enterprise AI leader with more than 20 years of experience across Google, Microsoft, and global technology companies. She leads enterprise AI strategy at Proofpoint, where she is building governance, observability, and platform architecture for AI adoption from the ground up. Her work focuses on the operating model behind enterprise AI, including how organizations govern agentic AI, manage AI tool sprawl, and scale adoption responsibly. Candice has spoken at women-in-tech events and led sessions with eWoW and PowerToFly, and is passionate about mentoring the next generation of women in technology. She holds a Master's in Computer Science and a Bachelor's in Computer Engineering, and is focused on helping enterprises move from AI experimentation to durable, well-governed operating systems.
What motivated you to join the AI Builders Global Conference?
I'm very excited to speak at the AI Builders Global Conference 2026. I've spent the last several years inside large enterprises trying to figure out how AI actually gets adopted, not just piloted. A lot of that work happens quietly, inside governance meetings and architecture reviews that never make it into a keynote. I wanted to join this community because it's one of the few spaces where practitioners are talking honestly about what's working and what's breaking, not just showcasing demos.
What shaped your journey through technology and AI?
I've spent over 20 years in tech, including time at Google and Microsoft, before moving into enterprise AI leadership. That journey took me from building products to leading large-scale technical programs, and eventually into standing up entire AI functions from scratch. What pulled me toward AI specifically was watching how much organizational energy gets spent on tools, and how little gets spent on the operating model around them. I wanted to work on that gap.
Why does agentic AI need governance rails now?
This topic is important to me because I'm living it! Right now I'm building governance for agentic AI inside a large enterprise, and the biggest risk isn't the technology itself, it's the assumption that existing IT controls will simply stretch to cover it. Agents don't behave like software, they behave like new employees with access and autonomy. If we govern them the old way, we'll either lock down innovation or miss real risk. I want to give people a practical way to think about this before it becomes a crisis.
Who should be part of this discussion?
CIOs, heads of AI strategy, and anyone responsible for enterprise architecture or governance. This isn't a talk for people evaluating whether to adopt agentic AI, it's for people who already have agents showing up in their environment, sanctioned or not, and need a framework to get ahead of it.