(00:00:00) Welcome to Data Science Show

(00:00:41) The Problem with Orphaned Pilots

(00:01:41) Aligning KPIs for Business Impact

(00:02:54) Productizing Your Model

(00:03:59) Ownership, Funding, and Governance

(00:05:01) Measuring ROI and Risk

(00:05:37) A Retail Case Study

(00:06:17) Leadership and Organizational Implications

(00:06:58) Practical Checklist and Negotiation Tips

(00:07:39) Closing Thoughts and Call to Action

Many enterprises stall after promising AI pilots because experiments lack product rigor, clear ownership, and instrumented ROI. In this episode Mirko delivers a compact, practical playbook for executives to convert pilots into repeatable, revenue-driving products. He focuses on the decisions leaders must make: aligning outcome-level KPIs to business objectives, designing a minimum viable model product with deployment and monitoring, establishing funding and governance, and instrumenting ROI and risk from day one. To ground the framework, Mirko shares an anonymized vignette: a retail client that cut stockouts by 12% and improved gross margin by 3% within six months after productizing a demand-forecast model. Listeners will leave with a prioritized 90-day checklist, negotiation language to secure executive buy-in, and a concrete CTA to download a two-page AI Scaling Checklist. This episode avoids code-level how-tos and vendor hype, concentrating on leadership moves that produce measurable value.

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I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions.
Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.