Enterprises had rapidly moved from AI experimentation to real, high-stakes deployment, and with that shift came a new challenge ensuring these systems operated responsibly, transparently, and in compliance with global regulations. Many organizations have strong Responsible AI principles on paper but struggle to translate them into day-to-day operational practices across distributed teams and complex technology ecosystems. This edition of Building with AI brought together leaders from global enterprises who had already navigated this complexity. They shared how their organizations built governance councils, established accountability frameworks, strengthened data foundations, and implemented monitoring mechanisms that supported AI at enterprise scale. The session highlighted real-world stories of how Responsible AI had been operationalized not as a one-off initiative, but as a repeatable system embedded into product development, data workflows, and business decision-making.

Attendees gained clarity on how leading enterprises had moved from conceptual conversations about ethics to practical execution models that ensured AI systems remained auditable, trustworthy, and aligned with organizational values. The event provided a comprehensive understanding of what “responsible at scale” looked like inside modern, fast-moving enterprise.