Organizations are facing increasing pressure to implement robust AI governance frameworks. The market portrays AI governance as an entirely new and complex domain requiring massive investment. Our honest no-bs perspective is different: AI governance need not be an overwhelming or complicated undertaking. Instead, organizations can achieve effective oversight by strategically extending their existing investments in data cataloging, governance frameworks, and knowledge graph architectures.

In this session, we’ll present a straightforward, practical approach to AI governance that builds on current capabilities, helping organizations achieve compliance and transparency without a new big-budget project. Our discussion will focus on three actionable principles that streamline AI governance: 

1. Catalog Everything: Capture all AI assets—including models, datasets, and policies—within a unified catalog to ensure visibility, accountability, and traceability across the organization.
2. Build Trust with Transparency: Use trust signals like data quality, lineage, bias, and compliance tracking to monitor and validate AI outputs, reinforcing reliability and accountability.
3. Enable Explainability: Leverage semantic relationships and lineage data to make AI outputs understandable, aligning them with business goals and stakeholder expectations.

By the end of this session, attendees will understand how to adopt a scalable, efficient AI governance approach that leverages existing data strategy and tooling, and see this working in a demo and learn from customer examples. They will be equipped to demystify AI governance within their organizations, making it accessible, cost-effective, and adaptable to future needs.

Speaker: Juan F. Sequeda

Juan F. Sequeda is the Principal Scientist at data.world. He joined through the acquisition of Capsenta, a company he founded as a spin-off from his research. He holds a PhD in Computer Science from The University of Texas at Austin. 

Juan is the recipient of the NSF Graduate Research Fellowship, received 2nd Place in the 2013 Semantic Web Challenge for his work on ConstituteProject.org, Best Student Research Paper at the 2014 International Semantic Web Conference and the 2015 Best Transfer and Innovation Project awarded by the Institute for Applied Informatics. Juan is on the Editorial Board of the Journal of Web Semantics, member of multiple program committees (ISWC, ESWC, WWW, AAAI, IJCAI). He was the General Chair of AMW2018, PC chair of ISWC 2017 In-Use track, co-creator of COLD workshop (7 years co-located at ISWC). He has served as a bridge between academia and industry as the current chair of the Property Graph Schema Working Group, member of the Graph Query Languages task force of the Linked Data Benchmark Council (LDBC) and past invited expert member and standards editor at the World Wide Web Consortium (W3C). 

Wearing his scientific hat, Juan's goal is to reliably create knowledge from inscrutable data. His research interests are on the intersection of Logic and Data for (ontology-based) data integration and semantic/graph data management, and what now is called Knowledge Graphs. 

Wearing his business hat, Juan is a product manager, does business development and strategy, technical sales and works with customers to understand their problems to translated back to R&D.

Speaker: Tim Gasper

Tim Gasper is Chief Customer Officer at data.world, where he leads the customer success, implementation, and support teams for the modern data catalog company. Previously, he drove product strategy as vice president of products at data.world. Tim is also a co-host of the popular data podcast, Catalog & Cocktails. Before joining data.world, Tim co-founded Opulent AI, a company focused on leveraging artificial intelligence and advanced automation. Tim has over 11 years of product management and product marketing experience across software, SaaS, and AI and analytics products, and is a writer and speaker on entrepreneurship, lean startup methodology, and big data analytics.