Is Self-Service BI a False Promise? Lei Tang of Fabi.ai Thinks So

Explore the future of AI-powered business intelligence with Lei Tang, CTO and Co-founder of Fabi.ai, as he discusses the evolution from traditional self-service BI to "Vibe-analytics." Learn how AI is transforming data accessibility, enabling anyone to perform sophisticated analytics without deep technical expertise. From building trust in AI-generated insights to creating intelligent semantic layers, discover how modern BI platforms are bridging the gap between data teams and business stakeholders. Tune in to understand why static dashboards are becoming obsolete and how AI agents will soon proactively surface business opportunities and insights.

Lei is the Co-founder and CTO of Fabi.ai, where he leads the development of AI-native business intelligence solutions. With a PhD in machine learning and over a decade of experience in the data domain, Lei has held significant roles, including positions at Yahoo, Walmart, Lyft (as Director of Data Science), and Clari (as Chief Data Scientist). His expertise spans machine learning, data engineering, and business analytics, with a particular focus on making data analysis more accessible and efficient. In this episode, Lei shares insights on the evolution of self-service BI and how AI is transforming business intelligence, drawing from his experience building Fabi.ai, a platform that combines SQL, Python, and AI to democratize data analysis. His work in developing "Vibe AI" (AI-powered BI) represents a significant advancement in making complex data analysis accessible to non-technical users while maintaining data accuracy and trust.

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"For the past decade, it's really difficult to make sure the self-service BI can work. And then now with AI, the worst part is that it can run properly, but the numbers are wrong." - Lei

"If you talk to anybody working in the BI space, like self-service BI, that has been termed for maybe for the past decade. But I have to say that is a false promise." - Lei

"We're saying that we really want those data team to be able to, like, say, what type of data is exposed to, like, say, less technical folks." - Lei

"In order to build AI native BI, I would say the focus should be how human interact with AI." - Lei

"We believe that, essentially, this BI system or, like, AI BI system would be more like a agent, and then it'll actually looking for, like, business opportunities and insight and surface to you." - Lei

"The one common theme I have been experiencing is that normally would work with other business stakeholders, could be marketing, could be operations, could be sales." - Lei

"We strongly believe that BI should be stored as code." - Lei

"Enterprise data tends to be very noisy, very complex." - Lei

"The semantics of itself becomes part of the context for the AI engine." - Lei

"Most organizations, the data, like the schema, the kind of business, like metrics and logic, has been constantly evolving." - Lei

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Previous guests include: Joseph Machado of Linkedin, Metthew Weingarten of Disney, Joe Reis and Matt Housely, authors of The Fundamentals of Data Engineering, Zach Wilson of Eczachly Inc, Megan Lieu of Deepnote, Erik Heintare of Bolt, Lior Solomon of Vimeo, Krishna Naidu of Canva, Mike Cohen of Substack, Jens Larsson of Ark, Gunnar Tangring of Klarna, Yoav Shmaria of Similarweb and Xiaoxu Gao of Adyen.

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