The ability to transform a creative idea into a working concept is becoming accessible to a much broader audience. That is a remarkable development, but it should not be confused with the ability to build production-ready solutions. Building complex applications with the right architecture, security, governance, scalability and operational guardrails still requires deep professional expertise.
In fact, I would argue that the more powerful AI becomes, the more important that expertise becomes. The narrative around AI is often framed as if developers are somehow becoming less relevant.
I believe the opposite is happening.
As organizations increasingly rely on AI, expertise shifts rather than disappears. Teams need to understand how different models behave, where their limitations lie, how outputs should be validated, how token consumption can be optimized, how data should be protected and how compliance requirements can be met. They also need to make informed decisions about governance, accountability, ownership and operational reliability. As AI becomes more deeply embedded in products and services and are more verticalized, these responsibilities only become more important.
Last week, we hosted a Vertical AI Immersion Day, bringing together management teams from across our divisions alongside our group leadership team.
The goal wasn't simply to talk about Vertical AI. It was to experience it.
Like many organizations, we've spent the past year discussing the opportunities and implications of AI. Across industries, boardrooms and product teams, the conversation seems unavoidable. Every strategy session, technology roadmap and conference agenda includes AI in one form or another.
And for good reason. We are witnessing one of the most significant technology shifts of our generation.
But as I listened to the discussions and observed the experiments throughout the day, I found myself reflecting on a different question.
What is the actual change we're facing?
Not from a technology perspective, but from an organizational and human perspective.
Much of the public discussion around AI focuses on productivity. AI can generate code, summarize information, create presentations, analyze data and automate tasks. The assumption often follows that we will simply become faster, more efficient and more productive.
There is certainly truth in that. But I increasingly believe that focusing only on productivity, risks missing the bigger opportunity and perhaps the biggest challenge.
For organizations like Topicus, the more important question is where expertise creates value in an AI-driven world.
That realization became particularly clear during our Immersion Day. As part of the event, we organized a mini hackathon. Our leadership teams were divided into small groups and challenged to create an entirely new application within just a few hours.
The results were remarkable.
Teams rapidly transformed creative ideas into working concepts. Applications that would previously have required significant technical effort were suddenly within reach. The speed at which people were able to move from an idea to a functioning prototype was genuinely impressive.
What stood out to me was not the technology itself. It was how quickly creativity translated into something tangible.
People whose primary responsibilities had shifted toward leadership, strategy and business outcomes were now exploring customer journeys, designing features, connecting systems and testing assumptions. The distance between an idea and a working application has become dramatically smaller.
That is incredibly exciting. It unlocks innovation and encourages experimentation. It enables far more people to contribute to solving customer problems.
However, it also led us to a second and perhaps even more important conclusion: Creating an AI-first application is one thing. Creating a trusted vertical software product that can operate in the real world is something entirely different.