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As organizations rush to scale AI, many are learning that better models can’t compensate for weak data foundations. AI hype is everywhere, but operational readiness still isn’t. In this episode of The AI Forecast, Paul Muller sits down with Ravit Jain, founder of The Ravit Show and one of the leading voices in the global data and AI community, to explore the trends shaping the future of enterprise AI.

Understand how to close the gap between AI experimentation and enterprise production. Shub Agarwal, Founder of the AI Trust Lab at USC and author of Successful AI Product Creation: A Nine-Step Framework, shares his AI product management framework for taking enterprise AI strategy from demo to production, drawing on two decades of product leadership at Amazon and Fortune 50 firms. He breaks down why experimentation must tie directly to business OKRs, the four mindset shifts leaders need to scale AI responsibly, and how the AI Trust Lab is building a benchmark evaluation framework for AI model trust and governance.

Welcome to Part 7 of the “Data Products for Qlik Analytics” series! In this episode, we take Data Quality to the next level by building advanced data validation rules using IF / THEN / ELSE logic within Qlik Analytics. You’ll learn how to create conditional validation logic that evaluates relationships across multiple columns, enabling smarter and more dynamic data quality checks for your data products.