Artificial intelligence is rapidly becoming a factor in industrial decision-making. But how can foundry companies determine where AI can create real value, and how should managers approach the opportunities and responsibilities that come with it? We discussed these questions with Ingo Bitzer, drawing on his extensive experience in the automotive supply and foundry sectors.
Bitzer has spent more than 30 years in senior management roles across the automotive supplier and foundry industries. As Managing Director, COO and CEO, he has consistently focused on the same fundamental objective: strengthening companies’ competitiveness, profitability and long-term readiness. His responsibilities have included automation and digitalization, Industry 4.0, advanced manufacturing technologies, strategic investment decisions and the development of international production facilities.
Today, Bitzer is using this background from a different perspective. As a strategic sparring partner and AI Executive Guide, he advises business leaders on the growing role of artificial intelligence. Rather than representing a completely new direction, he sees this work as a continuation of the challenges he has addressed throughout his career: understanding technological developments, evaluating their business potential and turning them into practical strategies for the future.
Making Companies Fit for the Future
“Our goal has always been to prepare companies for the future. Ultimately, only financially successful businesses can safeguard jobs in the long term.”
Over the course of his career, Bitzer has witnessed major changes in the economic landscape. One development that particularly stood out to him was the changing relationship between OEMs and suppliers in the European automotive sector. What were once often long-term partnerships have increasingly evolved into relationships where cost considerations take centre stage.
At the same time, energy-intensive industries such as foundries, forges and other primary manufacturing businesses are facing additional challenges. High energy costs, geopolitical instability and increasingly demanding regulatory requirements are putting growing pressure on companies and their ability to remain competitive.
Against this backdrop, Bitzer came to the conclusion that many of the challenges facing industry today cannot be addressed through more efficient machinery or optimized production processes alone. This was also when artificial intelligence increasingly entered his field of interest.
His initial view of AI, however, was far from enthusiastic. During his last management positions, he was repeatedly confronted with projects presented as artificial intelligence solutions. When he examined them more closely, he often found that they were essentially conventional databases or statistical evaluation tools rather than genuine AI applications.
Bridging the Gap Between Industrial Expertise and AI
“When I am asked to approve investments worth millions, I need to know exactly what I am investing in.”
This attitude prompted Bitzer to take a much closer look at the latest developments in artificial intelligence. He began studying modern AI technologies in greater depth and today maintains close contact with developers working on the next generation of intelligent algorithms.
At the same time, he noticed a shift in how business leaders approached him. Increasingly, companies were turning to him not in his former capacity as a managing director, but as an independent advisor on strategic decisions, investments and transformation initiatives.
A particularly revealing conversation took place with a long-standing entrepreneur and friend who also sits on the supervisory board of a major German company. He admitted that he was being asked to make investment decisions involving artificial intelligence without having a clear understanding of the underlying technology. For Bitzer, this illustrates a widespread challenge: companies are increasingly aware of AI's importance, but many decision-makers still lack a practical and accessible understanding of what the technology can actually do.
This gap is where Bitzer sees his role. He aims to connect two worlds: industrial business experience and technological expertise. His background allows him to assess new technological possibilities from a business perspective, while also helping experienced executives understand the terminology and concepts used by AI developers.
The foundry industry, in his view, offers particularly promising opportunities. Modern production systems generate vast quantities of process data, while increasingly complex processes and rising quality requirements create a strong basis for intelligent assistance systems. One example is the direct combination of low-pressure die casting with online X-ray inspection. Here, AI can assess component quality in real time and feed the results directly back into the process to adjust casting parameters.
Bitzer does not regard such applications as distant possibilities. Instead, he sees them as the next stage in a development that has progressed from mechanization and automation through digitalization and Industry 4.0 to artificial intelligence. An important point for him is that this development must not be limited to large corporations. Medium-sized industrial companies can also benefit considerably from a strategic approach to AI—whether by improving processes, increasing quality or safeguarding valuable knowledge accumulated over many years.
Today, Bitzer deliberately positions himself at the intersection of these two environments. On one side are established industrial companies with extensive manufacturing expertise; on the other are innovative start-ups and developers creating new AI solutions. His role is to connect these perspectives and help companies make informed decisions as they navigate a period of far-reaching technological change.
AI Requires More Than Technology
“Artificial intelligence does not start with algorithms. It starts with people who know how to use them responsibly.”
For Bitzer, this principle goes beyond his personal approach, instead, it reflects one of the key challenges companies face as artificial intelligence becomes increasingly important. The capabilities of an AI system alone will not determine whether its use creates lasting value. What matters just as much is whether people understand the technology, recognize its opportunities and limitations, and incorporate it thoughtfully into their business processes.
Ultimately, successful AI adoption depends not only on intelligent algorithms, but on the people making decisions about how and where those algorithms are used.
