Pfullendorf, August 31, 2026 – Artificial intelligence is here to stay. Hardly any other technology topic is discussed so intensely and loaded with such big, yet at the same time diffuse expectations. Companies need to distinguish between real benefits, inflated promises, and short-lived trends. What can AI already do today? Where does it create measurable added value? And what conditions need to be met to turn an idea into a successful project? These questions are at the heart of the latest episode of SPIE AutoMate.
Why companies haven’t missed the boat
Dr. Michael Kröhn, Senior AI Engineer at SPIE AUTOMATION, talks about his experience from industrial practice. In doing so, he clears up some of the most common misconceptions around the topic and explains why many companies have by no means already fallen behind when it comes to getting started with AI. Instead of being driven by hype, FOMO, and ever-new trends, he argues for a pragmatic view of the technology. It’s not speed that determines the success of an AI project, but the ability to identify meaningful use cases and create sustainable added value from them.
How successful AI projects come about
A key focus of the episode is the question of how successful AI projects come about. Why do some applications make it into production use while others fail already at the concept stage? The answer often lies less in the technology itself than in the framework conditions: data quality, clearly defined use cases, and business objectives play a decisive role. Using concrete examples from industrial environments, Dr. Michael Kröhn explains how an AI project is developed—from the initial idea through proof of concept to productive operation—and which challenges need to be overcome along the way.
Creating added value
In addition, the episode looks at the practical benefits of AI in day-to-day business. It shows where artificial intelligence can create real added value: from intelligent assistants and automated content creation to process data analysis and image processing. At the same time, it becomes clear that successful AI projects do not thrive on spectacular visions of the future, but on pragmatic solutions to specific problems. Often it is not groundbreaking revolutions, but continuous efficiency gains that deliver the greatest economic benefit.
Skill set in the AI era
Another important topic block deals with the skills people need when working with AI. Which competencies will become more important in the future? What role do critical thinking, curiosity, and basic technical understanding play? And how can companies bring their employees along through this change? The conversation makes it clear that the future is not determined by technology alone. People remain a central success factor. They must be able to put results into context, make decisions, and use the possibilities of AI responsibly.
Red Flags
Of course, the critical perspective is not neglected either. Dr. Michael Kröhn talks about unrealistic expectations and questionable marketing promises. He also addresses hallucinations in AI systems and how to handle data protection and data security. Instead of alarmism or blind enthusiasm, the AI expert argues for a nuanced view of the technology. His message: companies should view AI neither as a miracle weapon nor as a threat. It is a tool whose success depends on the people, processes, and data behind it.
Shaping AI use with a sense of proportion
The episode offers a well-founded introduction for all industrial companies that are taking a closer look at the topic for the first time. It also provides exciting food for thought for those who are already planning or implementing AI projects. It shows how companies can identify opportunities, assess risks realistically, and shape technological change with a healthy dose of calm. The first steps don’t have to be taken alone. SPIE AUTOMATION’s AI expert team knows the field inside out. It can help you get clarity on your starting point and tap efficiency potential in a targeted way.
