Generative AI has captured global attention, but most organizations remain stuck in pilots, proofs of concept, or disconnected experiments. In this keynote, Pedro Uria-Recio cuts through the hype and explains what it actually takes to move from GenAI experimentation to agentic AI systems operating at enterprise scale.

Drawing on real-world deployments from banking and other regulated industries, Pedro shows how leading organizations are designing, governing, and scaling AI agents that perform complex tasks, collaborate with humans, and deliver sustained business impact. He addresses the technical, organizational, and cultural shifts required to make agentic AI work in production, not just in demos.

This session is practical, honest, and grounded in lessons learned from deploying AI where reliability, trust, and accountability are non-negotiable.

Audience takeaways

• A clear understanding of the difference between GenAI demos and production-grade agentic AI

• Real examples of how AI agents are deployed safely in regulated environments

• The operating models, data foundations, and governance needed to scale agentic AI

• Common pitfalls that cause AI initiatives to stall — and how to avoid them

AI is already reshaping business, work, and society, but not always in the ways headlines suggest. In this keynote, Pedro Uria-Recio offers a grounded, strategic perspective on how AI is transforming organizations, labor markets, geopolitics, and decision-making, based on what is actually happening inside enterprises today.

Rather than speculation or science fiction, Pedro focuses on real deployments, real trade-offs, and real consequences. He explores how AI is changing the nature of leadership, competitive advantage, and human expertise, and what this means for executives, professionals, and institutions over the next decade.

This keynote helps audiences move beyond fear and hype toward a clear-eyed understanding of how to prepare for an AI-shaped future.

Audience takeaways

• A realistic view of how AI is already changing business and work

• Insights into where AI will create advantage and where it will not

• How leaders should rethink skills, organization design, and decision-making

• A practical framework to prepare people and institutions for long-term AI impact

As AI becomes embedded in core business processes, governance and trust move from compliance topics to strategic priorities. In this keynote, Pedro Uria-Recio explains how organizations can deploy AI responsibly at scale without slowing innovation or creating unnecessary bureaucracy.

Based on his experience leading AI governance across multiple countries and regulatory regimes, Pedro shows how trust, risk management, and innovation can coexist. He demystifies AI governance, moving it from abstract principles to concrete structures, processes, and decision rights that actually work in large organizations.

This session is especially relevant for senior leaders navigating regulation, reputational risk, and ethical responsibility in the age of AI.

Audience takeaways

• What effective AI governance looks like in real enterprises

• How to balance innovation speed with risk, regulation, and accountability

• Practical approaches to model risk, explainability, and responsible AI use

• How trust becomes a competitive advantage in AI-driven organizations

Many organizations invest heavily in AI but struggle to show tangible returns. In this keynote, Pedro Uria-Recio shares a practical framework for turning AI from a cost center or innovation experiment into a consistent driver of business value.

Pedro explains how to prioritize the right use cases, align AI initiatives with strategic objectives, and build the organizational capabilities needed to move beyond pilots. Drawing from large-scale enterprise transformations, he shows what separates AI programs that deliver ROI from those that quietly fade away.

This keynote is designed for leaders who want results, not buzzwords.

Audience takeaways

• A clear framework to prioritize AI use cases based on business impact

• How to move from pilots to scaled deployment across the organization

• Metrics and governance models that enable measurable ROI from AI

• The leadership behaviors and structures required to sustain AI value over time