What Every Data Leader Should Know About Third-Party Data for AI and Analytics

AI has raised the stakes for data quality, coverage, and context. Organizations are discovering that first-party data alone is often insufficient to train reliable models, enhance analytics, or support AI-driven decisions at scale. Third-party data fills those gaps—bringing real-world context, broader attributes, and new dimensions to your analytics and AI workflows that internal data often can’t provide on its own.

This session will walk through the role of third-party data in modern data strategies, with a focus on how it strengthens AI, analytics, and operational initiatives. Whether you’re evaluating external datasets and data enrichment capabilities for the first time or scaling your program, you’ll learn what to look for in a third-party data partner and how to unlock value fast.

Key takeaways:

• Why third-party data is essential to improving accuracy, completeness, and relevance in AI and analytics
• What makes third-party data “AI-ready” and how to evaluate options
• Real-world examples showing how enriched data improves AI, analytics, and operational outcomes across industries
• Practical steps to start small, move quickly, and scale with confidence