Solution Lab: Building AI-Ready Semantic Foundations for Enterprise Analytics
Webinar Speaker: Donald Farmer, TDWI Research Fellow
Date: Thursday, November 5, 2026
Time: 9:00 a.m. P.T. / 12:00 p.m. ET
Conversational analytics and AI agents are changing who asks questions of enterprise data. People who never had a BI license can now ask questions in plain language, and agents can run a series of queries without a person reviewing each step.
Yet generative AI produces a fluent-sounding answer whether or not the number is right, and new users are often the least able to spot an error. Because an agent uses each result as input to the next query, errors compound: 90% accuracy per question falls to about 59% over five dependent questions.
TDWI research finds that 66% of organizations call a semantic layer critical, but only 19% have one. Most enterprises already have several semantic models, each built into one BI tool or platform, and they often give different answers. What is missing is one governed semantic layer that computes metrics the same way for every tool and agent. Using this research and real-world examples, this webinar shows how organizations can build and govern that layer.
In this TDWI Solution Lab, research fellow Donald Farmer gives an independent view of semantic layers for AI and the relevant TDWI research. An AtScale and Precisely specialist will show demonstrations of a governed semantic layer giving the same answers to BI tools and AI agents, and will join Donald for a discussion of how organizations are building these foundations today and what comes next.
Data and analytics leaders who need consistent, auditable AI answers will learn:
- Why a fluent AI answer can still be wrong, and why errors compound across agent queries
- What differentiates a universal semantic layer from catalogs, glossaries, and BI-specific semantic models
- How a central team and business domains can share ownership of metric definitions
Guest Speakers
Ryan Siegler
Developer Relations
AtScale
Ryan Siegler leads developer relations at AtScale, where he helps data and AI teams build on a universal semantic layer. A former AI and security engineer at Ford who went on to lead DevRel at KX, he focuses on closing the gap between what a platform can do and what developers ship with it. He is an advocate for the universal semantic layer as the foundation that gives AI agents governed, business-ready data.
Shantanu Sharma
Senior Product Manager
Precisely
Shantanu Sharma is a product lead at Precisely working on Suite Foundation AI team, the platform layer powering agentic and GenAI capabilities across the Data Integrity Suite. Earlier in his career, he led the data discovery and data governance offering at OneTrust, helping enterprises adopt emerging technologies while meeting privacy and regulatory requirements. His current focus is on helping enterprises operationalize AI on top of trusted data and expanding the platform so customers can access Precisely’s capabilities through the agentic tools they already use, including Claude, ChatGPT, Cursor, and others. He is based in Florida.
Antonio Cotroneo
Senior Director, Product Marketing
Precisely
Antonio Cotroneo is a senior director of product marketing at Precisely, focusing on the Data Integrity Suite, Location Intelligence, Data Integration, and Data products. He has spent his career helping people worldwide maximize their data, technology, and analyses to make critical decisions for their customers and communities. He lives in Charlotte, NC, with his wife and two children.