Conference Agenda
Presenting organizations include
Zach Wahl
Zach Wahl of Enterprise Knowledge opens the 2026 Semantic Layer Symposium, welcoming attendees and setting the stage for a day of deep dives into semantic architecture, AI readiness, and enterprise knowledge strategy.
Ole Olesen-Bagneux
AI makes searching for data easier. Translating a complicated topic into a search statement was once a laborious task requiring correct keyword syntax, special operators, and logically crafted search semantics. With the rise of AI, conversational search now allows complicated topics to be phrased and searched for in simple, natural language. This is a positive outcome: more employees can search for more data. However, what happens to the tacit knowledge required for crafting a complicated search statement? This presentation focuses on the role of tacit knowledge in an AI search era, and discusses whether conversational-style search is as easy as it seems.
Nicolas Seyot
As AI enables more and more of our decision‑making, trust will increasingly shift from models to data itself. We will explore the semantic layer as an enablement and trust‑building mechanism, discussing how semantic models, curated datasets, and knowledge graphs help create shared meaning, foster strong governance, and enable business professionals, applications, and AI to reason over data with greater confidence.
Rosanna Stephens
The bottleneck wasn’t missing knowledge. It was knowledge that AI couldn’t use. Adobe is transforming HR services to make the everyday effortless and rise to meet the moments that matter. Rosanna shares what the data revealed and how it drove a content, taxonomy, and governance redesign for AI that actually works.
Noz Urbina
Malcolm Hawker
Amy Duncan
Ben Clinch
Joe Hilger brings together practitioners and leaders from across disciplines who have designed, built, and scaled semantic layer solutions in the real world — across different industries, different maturity levels, and different definitions of success. The conversation will cover what actually works, what gets harder than expected, where AI is changing the equation, and what they wish they had known at the start.
Dr. Martin Romacker
Ilian Uzunov
A “true” semantic layer transcends pure technical and business lineage. It requires governed semantic assets: ontologies, metadata, FAIR vocabularies, and GUPRIs. Moving beyond string-based approaches to highly engineered, concept-based models makes data truly AI-ready. Using graphDB for 6+ years, Roche has built a scalable RDF infrastructure transforming data assets into actionable knowledge — showing how semantic connectivity provides the strategic foundation for enterprise-scale intelligence.
Karthikeyan Palanisamy
Enterprises invest heavily in AI, automation, and semantic technologies yet struggle to deliver value because these systems remain disconnected from frontline human knowledge. This presentation positions Knowledge-Centered Service (KCS) as the connective tissue between human knowledge work and semantic enterprise architectures. By treating KCS articles as validated, contextualized semantic assets, organizations can implement real-life problem-solving in Semantic Enterprise Architectures.
Lulit Tesfaye
Lulit Tesfaye of Enterprise Knowledge closes the day, reflecting on the key themes explored throughout the symposium and looking ahead to the future of the semantic layer movement.