Over the past decade, organizations have rapidly expanded their cloud, data, and AI footprints. More platforms. More dashboards. More automation. Yet many teams report increased operational complexity, slower decision-making, and rising skepticism about return on investment.

This session explores why technical advancement alone does not guarantee progress—and how intentional system design can restore clarity, trust, and value. Drawing from real-world enterprise, healthcare, and research experiences, the session reframes cloud and AI architecture as socio-technical systems shaped as much by human behavior, incentives, and governance as by tools.

Participants will examine common failure patterns behind “more-is-better” strategies, learn how to recognize misalignment early, and walk away with a practical framework for designing cloud and AI ecosystems that are purposeful, resilient, and aligned with real outcomes rather than activity metrics.