What a time to be alive: my eureka moment between AI, business and being human

Last Friday morning, everything I had been considering over the previous six months suddenly came together: new professional roles, my own business, family life, the much-discussed transformation, working with AI and how we develop as people and learn to be human again. It was my own eureka moment. Everything connected, made sense and pointed in a clear direction. So clear that I could not settle and had to start writing at 4.30 in the morning. The thoughts were arriving faster than I could type.

It began with a project I had been supporting for around a month, commissioned by Bregenz Tourism & City Marketing: developing a new congress format for Bregenz and establishing it in the market. I was at the stage of building the essential case for the city, local businesses and the organisation’s governing bodies. The central question is simple and uncompromising: what does it cost, and what does it deliver? In other words, what is the business model?

That question has occupied me for almost 20 years because these figures shape decisions. Better decision-making is central to my work. For just as long, I had wanted a tool that could quickly adjust ticket prices, attendance, overnight stays, sponsorship, public funding, venue costs and other variables; model scenarios; expose risks; and compare them with the value created for a town or region. A tool that enables thinking as well as calculation.

As a self-employed consultant, this was a particularly pressing issue. I no longer had the resources for lengthy studies or expensive impact calculators. I knew the situation from previous roles: knowing what is needed without being able to provide the evidence required for the decision. I had considerable respect for that moment.

Influenced by Raphael Gielgen’s DECODING FUTURES workshop and Wolf Lotter’s view that machines should serve people, rather than the reverse, I opened an AI tool that Friday morning and put 20 years of experience into a prompt. I pressed Enter, fetched another coffee and looked out of the window.

When I returned, I almost dropped the laptop. On screen was the tool I had been working towards for so long: complex financial models, strategic suggestions, adjustments whenever parameters changed and a visual dashboard. Two or three further prompts produced an interactive application that was already around 60 per cent developed. I could test scenarios, vary assumptions, understand risks and hold informed discussions. Created by AI, prompted by a human: me, occursus, with roughly as much knowledge of programming as Max the beaver has of flying. Eureka!

The important lesson is why this application came into being. It was not because I knew how the tool worked. It was because I understood the market, could interpret context, knew political dynamics, had a feel for decisions and understood when and how digital technology could be useful. That is the distinction.

Yet the problem was far from solved. A solution was closer, but the real work was only beginning: making decisions, implementing changes and taking responsibility after the tool, dashboard and model had been created. These are fundamentally human abilities. AI cannot relieve us of them. Resources should be directed towards implementing what emerges, as well as towards developing the next decision-making tool.

It also became clear how my own role had changed. I could now say with confidence what I earned my living doing: helping people understand problems, place them in context and solve them. This is what Wolfgang Bach describes as productive critical thinking.

The insight extended beyond business. It changed my view of family life, education and my children’s future. Learning to operate AI is not what will secure their place in the labour market. That familiar narrative is far too narrow and, in my view, nonsense. Learning to relate to other people and allowing creativity to flourish matter much more. As John Hattie’s thinking can be paraphrased: the purpose of school is to help people learn, rather than simply transmit knowledge.

There is a striking paradox. We invest enormous resources in training AI — helping machines learn — while forgetting to learn ourselves. Rediscovering curiosity, the pleasure of discovery and different ways of thinking should be a priority. Nico Acampora’s PizzAut restaurants in Italy particularly impress me. He deliberately employs autistic people: people who think differently, show genuine emotion and bring a smile to guests’ faces. Or the boy in SRF’s Mona mittendrin programme about children in psychiatric care, who serves the presenter coffee with such warmth that he creates something no machine can reproduce: love and connection.

Why take the argument so far? Because a seemingly small encounter with an AI application revealed something much larger: what is worth getting up for, working for and defending. We live in an exceptionally exciting period. But the possibilities need to be understood properly, without believing every fool who claims AI will automatically make everything better.

One simple conclusion remains. People still make things better: through empathy, curiosity, a desire to learn and a willingness to be there for others.

That Friday morning changed something for me. It leaves me looking ahead with enormous confidence. What a time to be alive.