Expert Panel: Observability in the AI Era: Delivering Transparency and Trust Across Data and Models
Webinar Speaker: TBD
Date: Monday, February 23, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
As AI systems become more complex and autonomous, the need for end-to-end observability is becoming critical. Observability provides visibility into the health, performance, and behavior of data pipelines, models, and AI agents—helping organizations ensure that outcomes remain reliable, explainable, and aligned with policy. In the AI era, observability must go beyond traditional data monitoring to include the full analytics and model lifecycle, from data ingestion and feature creation to model drift and agentic decision-making.
TDWI research finds that most organizations are still early in implementing AI observability, often relying on siloed tools that monitor data quality or model performance separately. In this TDWI Expert Panel webinar, we will discuss how a unified approach can help deliver transparency and trust across both data and models while supporting governance and compliance goals. Topics include:
- The expanding scope of observability in data, analytics, and AI
- Techniques for monitoring data quality, model behavior, and agentic actions
- How observability supports responsible and explainable AI
- Integrating observability into data and model operations (DataOps and MLOps)
- Frameworks for unifying monitoring, governance, and trust across the AI lifecycle
Date: February 23, 2026
Time: 9:00 am PT