Tobias Zwingmann's Linkedin Analytics

I didn’t start my AI/ML journey doing “Profitable AI”. I started it as a Data Scientist who built models that looked impressive on paper: – Customer churn prediction with 95% accuracy ✅ – Next-best-offer systems with 15% uplift ✅ – Data-driven B2B products generating 6-figure revenues from day one ✅ But the hard lesson I’ve learned after 10+ years at the intersection of business and technology is that none of this matters if you can’t show results on the bottom line. I’ve spent the last 5+ years in applied AI consulting where my work has taken me inside global enterprises in automotive and insurance, mid-sized companies with 500–1,000 employees, solopreneurs aiming to double their output, and small business owners uncovering $10k+ monthly savings in unexpected places. The contexts differ, but the patterns of what makes AI succeed (and fail) remain remarkably consistent. Success is not about: - Chasing the next shiny AI tool - Hiring data scientists from Silicon Valley - Hoping IT will figure it out It’s about applying the principles of Profitable AI to deliver outcomes that matter: doing things faster, at lower cost, with higher quality — or scaling what you do to entirely new levels. Along the way, I’ve shared many of these lessons in my books AI-Powered Business Intelligence (O’Reilly, 2022) and Augmented Analytics (O’Reilly, 2024), as well as in my weekly newsletter that is now read by 10,000+ professionals at companies like Google, Amazon, Gucci, H&M, Santander, and Mercedes-Benz. So If you’re tired of the shiny AI demos and want to see it deliver real results instead — I think you found a good place.