Xebiacon: Where AI moves from ambition to execution

AI has moved beyond experimentation. But for many organizations, impact is still out of reach.

Despite significant investment, most enterprises are still struggling to translate AI into measurable outcomes at scale: across engineering, data, and the way work actually gets done.

The gap is no longer about access to technology. It’s about execution.

Xebiacon brings together leaders and practitioners who are closing that gap, sharing how AI is being applied in production, what it really takes to scale, and where most organizations still fall short.

Hosted by Xebia, an AI-first consulting, software engineering, and training company, with 25 years of experience, the event is built on a simple premise: real progress comes from building, measuring, and learning, not from talking about potential.

Because AI doesn’t transform organizations on its own, it exposes the gaps:

• in how software is built
• in how data is structured
• in how decisions are made
• in how organizations actually work

For this conference, we are looking for substance over storytelling.

We invite speakers to share real-world experiences around these topics: 

Accelerating Software Development in the AI Era

AI is reshaping software development at unprecedented speed, from coding and testing to deployment and operations. But faster code generation alone does not create better outcomes. The real challenge is redesigning the entire software delivery lifecycle to turn AI-driven speed into measurable business value.

This track explores how engineering organizations are evolving their platforms, practices, and operating models to succeed in the AI era. Show us real-world experiences, lessons learned, and practical approaches to scaling AI across modern software engineering.

Engineering Trusted Data Foundations for AI

AI is only as reliable as the data behind it. Yet many organizations are building AI initiatives on fragmented, inconsistent, and poorly governed data environments that were never designed for autonomous systems and real-time decision-making.

This track explores how organizations are modernizing data platforms, consolidating complex data landscapes, and building trusted foundations for AI. We want to dive into data architecture, governance, sovereignty, observability, and scalable modernization.

Architecting the Agentic Enterprise

Moving from AI assistants that support employees to AI systems that can independently handle tasks, coordinate workflows, and make decisions, we have to navigate where this creates real business value, and where maybe traditional automation is enough.

This track focuses on practical applications of agentic AI across the enterprise. Take the stage with the actual integration of AI into business processes, and showcase how you redesigned operations around more autonomous ways of working. 

AI-Ready Leaders and Organizations

Buying AI tools is easy. Redesigning how decisions are made, how teams operate, and how leaders lead is harder, and that’s where the real transformation happens.

This track is for leaders who have challenged outdated operating models, re-thought their leadership style, and built teams that can actually thrive alongside AI. Are you brave enough to share an honest story about organizational change, workforce transformation, cultural resistance, and new leadership approaches? Then you are ready for what it takes to prepare people, not just systems, for an AI-first future.