-
Expert Panel: AI Governance in Practice: Balancing Innovation, Risk, and Responsibility
In this expert panel webinar, we’ll explore how organizations are developing practical frameworks for AI governance that balance innovation, risk, and responsibility and the tools that can help.
February 2, 2026
learn more
-
Designing AI-Ready Data Platforms for Enterprise Scale
Join TDWI and Google as they discuss how organizations are modernizing their data platforms to improve data quality and trust, simplify access across hybrid and multicloud environments, and move AI initiatives from experimentation into production.
February 17, 2026
learn more
-
Expert Panel: Powering Next-Generation Workloads: Secure and Unified Access to Data
In this expert panel webinar, we’ll explore strategies and architectures that enable secure, unified access to data to power next-generation workloads.
February 18, 2026
learn more
-
Build & Scale Enterprise Agentic Workflows on Trusted Data Foundations
In this session, you will hear from TDWI analysts about current trends surrounding agentic AI adoption in the enterprise today, along with top hurdles and roadblocks. Experts from Informatica and AWS will share how to integrate semantic context via metadata-driven discovery, automated data quality, and master data management. Learn why solid data management foundations and context are critical to power the agentic enterprise, and how Informatica’s purpose-built data management agents help automate and power agentic workflows through MCP and multi-agent collaboration.
February 19, 2026
learn more
-
Data Ingestion in the AI Era: From Raw Tables to Semantic Insights
Join TDWI research fellow Evan Levy and data integration experts from Precog to discover how leading companies have successfully scaled their integration capabilities to overcome the operational complexities of modern AI environments.
February 24, 2026
learn more
-
The State of Data Quality
The State of Data Quality webinar will outline what it takes to achieve sound data quality for modern AI demands. This includes the organizational structures, skills, and governance models required to manage data quality at scale, as well as the technical underpinnings such as pipelines, architectures, and tooling that enable safe, effective AI deployment.
March 9, 2026
learn more