In this on-demand session, data leaders from Ryerson, Starbucks, and Quest Software discussed how organizations can deliver trusted data products that support the fast-growing needs of AI-driven business.

Using Tokio Marine’s experience as an example, the panel explored how a data product mindset is reshaping data teams, improving readiness for AI, and creating real business value.

Speakers

• Susan Laine, Chief Technologist, Quest Software
• Don Fleschut, Chief Data Officer, Ryerson
• Megan Brown, Director, Starbucks Data Office, Starbucks
• Moderator: Michael O’Donnell, Director of Product Marketing, Quest Software

Highlights from the discussion

• The impact of a data product mindset: Panelists shared how treating data as a product has helped them deliver higher-quality data faster and support AI more effectively.
• A cultural shift across data teams:  Adopting this mindset changes how teams work—from ownership and accountability to how they collaborate with the business.
• Delivery challenges and discoverability: While progress has been made, speakers discussed the ongoing challenges around data discovery, legacy systems, and maintaining trust at scale.
• What makes a strong data product:
  Clear purpose, documentation, governance, and usability were cited as key ingredients for successful data products.
• Measuring business value: The group highlighted metrics such as adoption, reuse, quality improvements, and how data products accelerate AI initiatives.
• The link between data products and AI: Panelists shared how data products support AI development—and how AI is beginning to help automate data product delivery.
• Looking ahead: The future of data products includes more automation, stronger governance, and deeper integration with AI strategies.