My perspective on AI in business is shaped by operating responsibility, not experimentation. I’ve worked with AI from multiple vantage points: as a C-level leader accountable for enterprise outcomes, as the executive owner of IT and information security, and as an advisor to companies building AI-native products for business use. As a C-suite operator, I’ve been responsible for decisions about technology adoption inside complex organizations—where questions of productivity, risk, security, privacy, integration, and change management all converge. I understand how AI tools affect not just efficiency, but trust, governance, and execution, because I’ve owned those tradeoffs directly. I’ve also applied AI inside people and operating functions, particularly across HR, talent, analytics, and employee experience. That work required balancing the promise of automation and insight with the realities of adoption, workforce impact, and ethical use. I’ve seen where AI meaningfully improves how work gets done—and where it creates friction when introduced without the right structure or context. In parallel, I currently advise companies operating in the AI space, giving me visibility into how tools are designed, positioned, and sold, as well as how they actually land inside real businesses. That dual view—builder and buyer, vendor and operator—allows me to help leaders cut through noise and make grounded decisions about where AI fits into their strategy and operating model. Clients work with me in this category when they want help making AI practical, responsible, and useful to the business. I bring an enterprise-grade lens to AI adoption, grounded in security, systems thinking, and organizational reality, and I help leaders make decisions that hold up across technology, people, and risk—not just in pilots, but at scale.