AI & Big Data Expo North America 2026

The models have been selected. The use cases have been defined. And yet, most AI programs stall at the same point — not because of the technology, but because the data powering it isn't ready, the engineering teams building it can't move fast enough, and enterprises struggle to operationalize AI agents at scale.

Getting AI into production requires three things most enterprises underestimate: data their agents can trust, engineering teams that can build and ship at the speed AI demands, and agentic enterprise architectures that turn AI from isolated pilots into operational capability. Xebia works across all three.

At Xebia, we believe enterprise AI only delivers value when it's grounded in governed data, built with AI-native engineering discipline, and designed for real-world agentic use cases. That means migration-ready platforms, unified data foundations, AI applied across the full software delivery lifecycle, and enterprise AI systems that can securely support workflows, operations, and decision-making at scale.

Whether you're building the foundation for your first AI agent or scaling an enterprise-wide programme, we look forward to meeting you at Booth #246 at AI & Big Data Expo 2026.

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From Fragmented Data to Agent-Ready: How Xebia Helps Enterprises Unify a Complex Data Estate and Build a Foundation for AI

📆 Tuesday, May 19 | 11:05am – 11:35am

Most organizations reach the same inflection point with AI: models are selected, platforms are in place, use cases are defined — but progress stalls. The root cause is rarely the AI itself. It's the data. With 44% of data leaders citing data quality as their number one AI obstacle, the pattern is consistent: siloed, inconsistently defined, ungoverned data becomes the bottleneck. While humans can work around these gaps, AI agents cannot, they act on what's available, making data quality and structure critical.

In this session, we share how Xebia helps enterprises unify fragmented data landscapes into governed, scalable foundations for AI. Drawing on real engagements, we'll show how implementing Medallion architecture, enforcing data contracts, and automating migration with built-in quality controls enables faster, reliable data access, delivered at up to 50% faster than traditional timelines and at 40% lower cost than staff augmentation without full re-architecture. You'll leave with the key architectural decisions, delivery approach, and an honest account of how combining purpose-built AI agents with expert engineering compresses what typically takes 12–24 months into a fixed-price, milestone-bound engagement.

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Speaker: Niels Zeilemaker
Global CTO at Xebia with broad experience across startups and global enterprises. Niels defines data tech stacks and drives architecture strategies, including data mesh implementations, to enable scalable and future-proof solutions.