This week on The Data Stack Show, AI entrepreneur Alberto Rizzoli shares his journey from early computer vision breakthroughs to leading the automation of back-office workflows at V7. The discussion explores the shift from bespoke model training to configurable AI solutions, the impact of automation on business roles, and emerging best practices for integrating AI into enterprises. Listeners will gain insight into how AI infrastructure is moving from labs to everyday businesses, which roles are most vulnerable or secure amid automation, and why future-proofing your career means focusing on creativity, first principles, and continuous improvement. Don’t miss it!

This week on The Data Stack Show, Ryan Dolley joins Eric and John to discuss his unique journey from playwriting to leading product strategy in the data industry. The conversation explores the evolution of business intelligence (BI), the growing influence of AI on analytics, and the shifting skill sets required for data professionals. Key topics include the challenges of adapting to rapid technological change, the importance of embracing engineering practices in BI, and the need for continuous learning. Listeners will gain insights into how AI is transforming data roles, why storytelling remains central to analytics, practical advice for thriving in a fast-changing industry, and so much more. 

This week on The Data Stack Show, Eric Dodds and John Wessel explore how AI is reshaping the data industry, focusing on the ongoing cycles of bundling and unbundling within data infrastructure. They discuss the potential for closed ecosystems like Notion to deliver personalized, integrated experiences and examine recent industry moves such as Fivetran’s acquisitions. The conversation also highlights the challenges faced by both startups and incumbents, the influence of enterprise customers on product development, and the enduring importance of trade-offs when choosing between bundled and unbundled solutions. Key takeaways include the complexity of implementing AI across platforms, the likelihood that market cycles will persist despite technological advances, and the need for organizations to carefully weigh integration, flexibility, and long-term risk when adopting new data tools.