For three years I watched it happen from a consulting seat. Clients who used to ask about churn models and demand forecasts started asking about RAG pipelines and chatbots. The energy left the room whenever tabular data came up. Everyone wanted to do something with their PDFs. Nobody wanted to touch the datasets where the actual business lives: the millions of rows and columns of tabular data that underpins every enterprise. 

Every enterprise AI deployment eventually hits the same wall. Not a technical wall. A trust wall. The customer says: "We can't send our data outside our environment." The AI vendor says: "We can't hand you our model, it's our core IP." Both sides are right. And until now, one side has always had to blink.

Jeremy Fraenkel, Founder & CEO of Fundamental, joined This Week in AI for a roundtable with some of the leading voices shaping the next wave of artificial intelligence. In this conversation, Jeremy shares his perspective on where AI is actually delivering value today, and where the industry is still missing the mark - particularly when it comes to structured, real-world data and enterprise decision-making.

For most of my career, I've worked with tabular data. As a data scientist, that's where the real value has always been: structured, business-critical data that powers decisions across every enterprise. Revenue forecasting, risk modeling, churn prediction, pricing. Behind all of it is tabular data. And yet, looking back on the past ten years, progress in this space has been surprisingly stagnant. Models improved incrementally and tools became more convenient, but nothing fundamentally changed.