AI, Infrastructure & the Human Factor – Insights from Prof. Benedikt Berger

AI promises speed, efficiency, and smarter decisions – but are we even ready to use it? In our recent Born & Keplerpodcast episode, Prof. Benedikt Berger, Junior Professor at the University of Münster, breaks down what it really takes to bring AI into the real world.

His research focuses on digital business models and human interaction with intelligent systems. The conversation offers a clear-eyed look at the gap between AI ambition and operational reality – and why that gap might be wider than many think.

❖ Infrastructure First – The Hidden Bottleneck

One of the most direct takeaways from the episode is this: most companies simply don’t have the infrastructure to use AI meaningfully.

"Before I can even think about using AI, I need the right infrastructure – and clean data."– Prof. Benedikt Berger

From fragmented systems to missing process digitization, many organizations are still dealing with foundational issues that prevent AI adoption from moving past the pilot phase.

❖ Decision-Making: Where AI Ends and Humans Begin

AI can suggest, predict, simulate – but should it decide?

Berger outlines a spectrum of human-AI collaboration, from simple decision support to full delegation. The key, he says, lies in understanding:

• How critical is the decision?

• How often does it repeat?

• What’s the acceptable margin of error?

"Who has the final say – the human or the machine? That depends on context, risk, and trust."– Prof. Benedikt Berger

Especially in high-stakes domains (e.g. finance, healthcare, public policy), the balance between algorithmic efficiency and human accountability becomes more than a technical question – it’s a social one.

❖ Avoiding the “Shiny Object” Trap

Berger also warns against chasing every new AI trend without a clear strategic lens. Researchers and companies alike, he says, often get distracted by what's new rather than what's needed.

This echoes a theme throughout the episode: focus on the problem, not the hype. It’s not about using AI for the sake of it – it’s about aligning technology with real organizational needs.

❖ What This Means for Leaders

For decision-makers, the message is clear:

• Build your digital foundation before investing in AI tools.

• Understand where human oversight is non-negotiable.

• Make sure your teams have the skills to evaluate and guide AI systems, not just deploy them.

It’s not enough to “add AI” to a process – we need to design systems where humans and machines work together, with clear roles and boundaries.

🎧 The full episode (German language) is now available on all platforms: 🔗 Spotify 🔗 Apple Podcast

Whether you’re a tech leader, strategist, or researcher – this is an episode that cuts through the buzz and focuses on what really matters when bringing AI into practice.