Data Quality

This webinar discusses the growing importance of data quality in the age of AI and how it is redefining information governance. Rather than focusing on compliance alone, the session positions data quality as a critical enabler of business outcomes, productivity, and successful AI adoption.

The presenters explain how organizations must rethink their approach to managing data, ensuring it is accurate, relevant, and properly governed to support reliable AI-driven decision-making and innovation.

Key topics covered include:

• The shift from compliance-driven governance to outcome- and productivity-driven strategies
• The role of data quality as the foundation for effective AI initiatives
• How poor data quality impacts AI results, costs, and reliability
• Real-world examples across industries (insurance, healthcare, oil & gas, life sciences)
• The information lifecycle and its connection to data quality
• Practical approaches to operationalizing data governance
• Building data pipelines, maturity models, and AI-ready data environments
• How organizations can create value, reduce friction, and improve efficiency using AI