Most AI teams are flying blind - they can show you how many people used their AI, but not whether it actually worked.

In this conversation, host Johannes Deubener sits down with Julien Roux, CRO and co-founder of Nebuly (the “Google Analytics for AI”) to unpack what relevant AI Analytics look like.

They explore why treating AI like traditional software (“build it, ship it, forget it”) is a fundamental mistake, and why AI needs to be managed as a living product: launched, observed, and continuously improved based on how people actually use it. Julien explains how most companies still rely on shallow metrics - logins, number of prompts, session duration - and why those can be dangerously misleading. In conversational AI, more usage can mean more frustration, not more value.

Chapters

00:05 Meet Julien Roux
02:23 From Mechanical Engineering to Finance
05:26 What “AI-Powered" Toothbrushes Mean
08:11 AI "Launch-and-Learn" Explained
10:50 From Investor to AI Founder: Why Julien Bet on AI Analytics
13:03 Executives’ Fantasy vs. Employee Reality in AI
16:57 Rocky Waters: Careers, Juniors, and the Future of Work
21:18 Pareto in Practice: Focus on the 10–15% of AI Use Cases That Drive 80% of Value
24:00 Why Traditional Analytics Fail for AI Assistants
29:21 “Google Analytics for AI”: What Nebuly Actually Measures
32:11 Explicit vs. Implicit Feedback in AI Conversations
36:18 100x More Actionable Feedback: The Iveco Case Study
38:50 Fixing AI Quality: Knowledge Bases, RAG, and the 80% Non-Technical Problems
41:16 Mining Business Signals from Customer-Facing AI (Churn, Upsell, Demand)
47:16 From Black Box to ROI: Turning Time Saved into Dollars
51:43 What CFOs Will Ask AI Teams in 2026
56:00 The Future of AI Analytics, Skills, and Infrastructure

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Don't be shy and come say hi:

Connect with Johannes: https://www.linkedin.com/in/johannesdeubener/

Follow Julien: https://www.linkedin.com/in/julienroux92/

Check out Nebuly: https://www.nebuly.com/

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