Data Quality and AI: Building Trustworthy Systems from the Ground Up

AI systems are only as strong as the data they rely on. As organizations race to adopt AI and automation, data quality has become a mission-critical foundation—not a nice-to-have.

Join DAMA Houston for an engaging session focused on how to build trustworthy AI and analytics systems by prioritizing data quality from the very beginning. We’ll explore the intersection of Data Quality and AI, practical governance strategies, and the real-world challenges organizations face as they scale AI responsibly.

💡 What You’ll Learn:

• Why data quality is the #1 driver of trustworthy AI
• The core data quality dimensions and how they impact AI model outcomes
• Practical frameworks for embedding data quality checks into data pipelines
• How tools support data quality and Responsible AI practices
• How to establish accountability across Data, AI, and business teams
• Real examples of data quality gaps leading to unexpected AI behavior—and how to prevent them

🎟️ Registration Required
Grab your lunch, log in, and level up your understanding of data quality in the age of AI. All registrants will receive the meeting link and event details.