Noz Urbina is one of the few industry professionals who has been working in what we now call “multichannel” and “omnichannel” content design and strategy for over two decades. In that time, he has become a globally recognized leader in the field of content and customer experience. He’s well known as a pioneer in customer journey mapping and adaptive content modelling for delivering personalized, contextually-relevant content experiences in any environment. Noz is co-founder and Programme Director of the OmnichannelX Conference and Podcast. He is also co-author of the book “Content Strategy: Connecting the dots between business, brand, and benefits” and lecturer in the Master’s Programme in Content Strategy at the University of Applied Sciences of Graz, Austria.
Noz’s company, Urbina Consulting, works with the world’s largest organizations and most complex content challenges, but his mission is to help all brands be able to have relationships with people, the way that people have with each other. Past clients have included Johnson & Johnson, Eli Lilly, Roche, and Sanofi Pharmaceuticals; Microsoft; Mastercard; Barclays Bank; Abbott Laboratories; National Geographic; and hundreds more.
The Role of Structured Content and DITA in Agentic AI & RAG
Panel Discussion Featuring:
Dawn Stevens, President, Comtech Services (moderator)
Wiegert Tierie, VP Strategic Accounts, RWS
Noz Urbina, Omnichannel Strategist, Urbina Consulting
Rob Hanna, CEO and Co-founder, Precision Content
Lief Erickson, Principal Content Strategist, Intuitive Stack
Harald Stadlbauer, General Manager, NINEFEB GmbH
Spotlight: How the Component Content Alliance (CCA) is Shaping the Future of AI-driven Content
The Component Content Alliance (CCA) unites industry leaders to explore how structured content, DITA, and metadata enable Agentic AI and next-gen Retrieval-Augmented Generation (RAG). Unlike traditional RAG, Agentic RAG allows AI agents to make decisions, interact with data, and generate more contextually accurate responses. To be business-ready, AI needs structured, reusable, and semantically rich content.
Why Attend?
- Learn how structured content improves AI-driven retrieval.
- Discover how DITA and metadata enhance GenAI performance.
- Avoid AI hallucinations and improve trust in AI-generated content.
- See how structured content cuts localization costs and accelerates publishing.
- Hear from CCA experts on the best practices and pitfalls.
If you work in AI, content strategy, or localization this session will provide actionable insights on making your content AI-ready.e.
In this panel discussion attendees will learn:
- How structured content fuels AI – The impact of metadata, tagging, and information architecture on retrieval accuracy.
- DITA & AI: A perfect match? – Why component-based content (DITA) enhances AI-driven applications.
- AI & enterprise content ops – Challenges and strategies for scaling structured content with AI.
- Real-world implementations – Case studies on AI-driven automation and content workflows.
The Role of Metadata in Managing Content in Unified Portals & AI Readiness
Metadata plays a crucial role in managing and retrieving content within a unified portal, enhancing searchability, distribution, access, and retention.
We will present the key Functions of Metadata:
Search and Discovery: Metadata allows users to search for content using specific criteria such as content type, product category or name making it easier to find relevant information. Consistent metadata tags across systems enable quick pinpointing of the right sources for analysis and visualization.
Distribution: Metadata values are used by applications to determine when and where content should be distributed or shared.
Access and Security: Security measures applied to managed objects are often integrated into the metadata model.
In this session, attendees will learn:
Core Components of Metadata Frameworks:
- Metadata Modeling: Structured standards offer baseline templates of metadata elements for descriptions, which organizations can extend to meet specific needs.
- Unified Metadata Foundation: Creating a common metadata foundation delivers insights and intelligence across all data sources.
- AI and Machine Learning: Applying AI and machine learning to unified metadata assists and trains AI as a powerful tool for AI based support. This AI training delivers an incredibly powerful AI ready repository that is a foundation for AI related projects such as AI driven chatbots.
