Decision Makers Roundtable – From AI Hype to Operational Impact
Decision Makers Roundtable – From AI Hype to Operational Impact
An invite-only (max 15 seats) breakfast roundtable for senior manufacturing leaders exploring how to move from AI experimentation to real operational impact.
Across industries, many organizations are actively testing AI, but turning pilots into scalable, value-generating systems remains a key challenge. This session focuses on what it actually takes to bridge that gap in practice.
The discussion is based on insights from 120+ real AI projects and brings together a small group of peers to exchange experiences, challenges, and lessons learned around AI readiness, scaling, and ROI in industrial environments.
The format is intentionally conversational and high-trust, combining short expert inputs from Jonas and Markus with open roundtable discussion among participants.
What we’ll talk about
Why many AI initiatives don’t scale beyond pilots
What “AI readiness” really means in manufacturing environments
The most common failure points when moving to production
What actually works when scaling AI in operations
Real examples from industrial use cases like maintenance, quality, and process optimization
Who should join
COOs, Heads of Production, Plant Managers, Heads of Digital AI Innovation, and Manufacturing Strategy Leaders from industrial, automotive, machinery, electronics, and related sectors.
Format
A small, invite-only roundtable with a maximum of 15 participants.
No presentations, no recordings — just open, peer-level discussion.
The session includes a short expert input, followed by moderated discussion and informal networking.
Breakfast, coffee, and drinks will be provided throughout.
Location
AI Campus Berlin
Agenda
09:00 – Arrival & Breakfast
09:30 – Welcome & Context (Jonas / Markus)
09:40 – Expert Input: Lessons from 120+ AI Projects
10:00 – Roundtable Discussion
10:20 – Key Takeaways
10:30 – Networking & Open Exchange
An open, practical conversation for leaders who are actively shaping how AI moves from experimentation into real operations.
About Your Hosts
Paul Rupprecht
Managing Director / Professional Services, Merantix Momentum
Paul focuses on helping organizations successfully implement and scale AI transformation initiatives, bridging strategy, operations, and execution. As Managing Director for Professional Services at Merantix Momentum, he leads enterprise AI engagements across industries and supports organizations in turning AI from experimentation into measurable business impact.
With more than ten years of experience in AI transformation and operational scaling, Paul has built and scaled multiple business units at Merantix Momentum and played a key role in shaping the company’s professional services organization. His expertise spans AI strategy, enterprise transformation, operationalization, and the integration of AI into complex business environments.
Paul holds an M.Sc. in Information and Automation Engineering and additionally serves as an AI Advisor to Merantix Capital
as well as a member of the AI Advisory Board at Cornelsen.
Senior AI Advisor / Manufacturing Lead, Merantix Momentum
Jonas focuses on bringing AI into real industrial environments, helping manufacturing companies move from experimentation to scalable, production-ready solutions. With a strong background in SaaS, sales, and industrial technology, he bridges the gap between technical capabilities and real-world operational needs.
Before joining Merantix Momentum, he held various commercial and technical roles across industrial software and engineering companies, consistently working at the intersection of manufacturing, data, and enterprise transformation.
Markus Gelfgren
AI Solution Architect, Merantix Momentum
Markus works on designing and delivering applied AI solutions for complex industrial use cases. His expertise lies in translating machine learning research into scalable, production-ready systems, with a strong focus on optimization, automation, and real-world impact.
Prior to Merantix Momentum, he worked in consulting and automotive R&D, including reinforcement learning for production scheduling at Mercedes-Benz and optimization projects across engineering and manufacturing environments.