As AI technologies, particularly LLMs, become increasingly integral to data management strategies, ensuring the quality and reliability of these systems' outputs is paramount.

Our experts will explore the critical role of foundational data quality in harnessing AI effectively and responsibly, and address key challenges, such as achieving consistency and accuracy in AI-generated outputs and aligning them with regulatory standards already on the horizon. Attendees will gain insights into practical applications of AI in the real world, understanding how to make AI outputs on data trustworthy across the entire organization.

By the end of the session, participants will be equipped with actionable strategies to navigate the intersection of technical innovation and regulatory compliance, ensuring their data is of the highest quality to leverage AI responsibly. Don’t miss this chance to advance your organization’s data capabilities and drive business innovation. Register now to secure your spot. 

Agenda: 

• The Importance of Data Quality in AI: Understanding the foundational role of data quality in AI effectiveness and common data quality challenges in AI-driven systems

• Exploring the Potential of AI in Data Management: How AI, including Large Language Models (LLMs), is transforming data management strategies and case studies of AI applications in real-world data quality scenarios

• Key Challenges in AI-Driven Data Quality: Ensuring consistency and accuracy in AI-generated outputs and addressing the alignment of AI systems with emerging regulatory standards

• Practical Strategies for Trustworthy AI Outputs: Best practices for making AI outputs reliable across an organization and actionable strategies for integrating AI responsibly within data management processes

• Q&A Session: Open floor for attendee questions and discussion of specific concerns and queries related to AI and data quality