AI agents reasoning across your biological and clinical data is a real prospect. But the path there is harder than vendors admit. The bottleneck isn't models or tooling; it's the semantic infrastructure underneath, and no AI can build it for you.
Join Jane Lomax to see where automation genuinely helps with ontologies, and where human expertise stays irreplaceable.
What we'll cover in this session
Why AI cannot automate ontology development, and what the platforms promising otherwise are getting wrong
Real examples from OBO Foundry that illustrate where automation helps and where it breaks down
The critical difference between a BI semantic layer and the ontological infrastructure agentic AI actually requires
Why a unified enterprise ontology is the wrong goal, and what governed federation looks like in practice
The scaling challenge no one is being honest about, and how leading organisations are managing it
Q&A
This is a practitioner's session. Expect candour, worked examples, and robust discussion. Our goal is to leave you with a clearer view of what's real, what's hype, and what your organisation actually needs to get right.
Who should attend
Data scientists, data engineers, data architects, bioinformaticians, and heads of data science who are evaluating, building, or governing semantic infrastructure for AI at scale.
Save your spot
July 8th • Live, with Q&A. Can't make it live? Register and we'll send the recording.
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