See how organizations move beyond AI pilots by aligning governance, data, sovereign AI infrastructure, and business goals to turn potential into proven, repeatable value, with support from Dell Technologies and NVIDIA. The session will end with a live demonstration of how we can bring strategy to life by building a tailored AI prototype in hours.​

AI is moving into core enterprise workflows, and most organizations already have access to models. The challenge is no longer access, but control.

In practice, model usage is often fragmented, with limited visibility into how models are used, what data they access, and how costs evolve. This leads to inefficiencies such as idle GPUs, duplicated usage, and unpredictable spend.

This keynote focuses on how organizations can regain control by centralizing model access through a Model-as-a-Service approach. This makes it possible to understand usage, enforce governance, and optimize cost, while keeping AI deployments private and under enterprise control.

Industry IT departments are stuck in analysis mode. This creates a false sense of control: while strategy is being aligned. AI has already entered daily operations—in ways that are neither centrally managed nor fully visible.

Engineers, planners, purchasers, and developers are already using AI to debug issues, summarize information, generate content, and support decisions, an activity that is largely invisible to management, creating a blind spot: the organization is evolving in fragmented ways while leadership assumes there is still time to evaluate options.

This gap drives the current hesitation across the industry. Leadership sees uncertainty and delays decisions, while employees move ahead pragmatically. Over time, this creates increasing exposure without corresponding oversight.

The task now is to surface and shape what already exists: make usage visible, focus on areas with proven impact, and secure the processes that matter most. This requires a shift in leadership from control to enablement.

AI is already part of daily operations. The question is whether companies take ownership of this development or allow it to unfold without direction.

Most organisations have AI projects running. Few can answer the question that matters most: what are we getting for the money?

This presentation tackles that problem directly, drawing on real experience building and operating an AI governance framework across a live enterprise portfolio. It is an account of what was built, why, how it works in practice, and what proved harder than expected.

The session covers the core components of an AI value playbook: a tiered classification model that applies proportionate governance to both new and existing projects, a four-checkpoint governance gate that must be passed before any AI initiative moves forward and a three-layer measurement framework that distinguishes between adoption, performance and value metrics.

As AI rapidly evolves, business leaders must look beyond current use cases to understand what’s coming next. This session explores the next wave of AI—from emerging technologies to shifting capabilities—and what it means from a strategic and board-level perspective. Drawing on deep analysis of both technology and business trends, it highlights key signals, future scenarios, and the decisions leaders need to start making today to stay ahead.

In recent years, enterprise architecture has shifted from governance and control to influence and enablement. But AI is changing the game once again.

We are entering a world where systems increasingly decide, recommend, and act—sometimes faster than humans can fully understand.

In this context, architecture can no longer be about enforcing standards or designing static roadmaps. Its true value lies in shaping how decisions emerge and ensuring the ecosystem is AI-ready and flexible in the face of change.

This keynote reframes architecture as a discipline of influence, decision design, and adaptability—essential for navigating AI-driven complexity.

In an era defined by data growth and agentic AI, effective risk management requires more than traditional controls. Dušan Tomić of WIPO presents a strategic shift toward data-informed security—where access decisions are driven by context, visibility, and governance. Discover how integrating IAM, master data, and data catalogs enables organizations to reduce exposure, strengthen compliance, and build a foundation for secure AI adoption

Dell Technologies and NVIDIA unveil the results of their live AI prototype demonstration and reflect on the journey from concept to execution. This session will highlight key insights, lessons learned, and feedback gathered during the event, offering a practical perspective on turning AI potential into proven success.