Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?

I have a German master's degree in mechanics, an engineering degree, and an MBA from Henley Management College in Henley-on-Thames.

I worked as a PD Engineer at Ford in Germany and the USA for 10 years. I moved into IT projects and managed SAP implementations for Visteon after the spin-off from Ford.

17 years ago, I moved from the automotive industry into the software industry when I joined Siemens Industry Software, where I have been leading digital transformation projects in complex industrial environments, primarily focused on PLM, ERP, and MES systems, as well as leading a consulting organization of roughly 100 people.

My last position title at Siemens was PMO Director DACH. Recently, I have started to lecture at a college on mostly MBA topics and product Lifecycle Management. I’ve also been exploring the deployment of AI agents to support cross-functional workflows in manufacturing and product development.

Q2. Which manufacturing segments or regions are demonstrating the fastest adoption and biggest gains from smart manufacturing, and what differentiates the top performers?

I believe the automotive industry always had and probably still has an edge over most other traditional industries. Auto OEMs are mostly monolithic, which makes the roll-out of best practices easier than conglomerates with multiple business lines. Also, top performers tend to be those companies that make change part of their culture.

Q3. Which types of companies or business models are emerging as new market leaders as a result of digital transformation?

Companies that can leverage digital transformation to enable reuse in all steps of the journey, from idea to production to decommissioning. The impact on the customers is configurable products that meet most of their needs at attractive prices.

Q4. Which specific Industry 4.0 innovations are likely to deliver the next wave of operational efficiency or cost disruption?

Agentic AI for sure

Q5. Which next-generation technologies are forecasted to have the greatest operational or market impact by 2030?

AI agents will be part of the workforce, taking over more and more white-collar duties at a fraction of the cost, leaving only the decision-making to the humans (initially).

Digital Twin concepts/vision are growing in popularity but contain a high amount of marketing by the SW vendors. The full DT of product and production in everyday use remains a dream for most.

Q6. What unique challenges do highly regulated industries face when implementing digital twins, AI, and automation into existing workflows?

Regulated industries are, well, regulated. That means any minute change to a formerly certified process, workflow, or piece of software entails recertification at a very high cost. What they want is well documented and hence easily certifiable SW that they can drop into their existing process and tool landscape without configuration or coding. The reality of the products that can deliver DT looks different.

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management?

To SW vendors that deliver DT tools: How do you facilitate the flow of data between your applications, your own AI offerings, and AI frameworks that your customers choose to deploy?

To all companies: Have you reviewed your business to understand which enterprise functions will be disrupted if not eliminated by AI?

Same question regarding their products.