Democratization of IT — as AI moves into management
AI has gone from technical curiosity to topping the agenda in boardrooms in a short time. Despite headlines about “new industrial revolution,” we're not here to spread the hype -- quite the opposite. In a sober but far-sighted spirit, it can be stated that AI is already rewriting the rules of business logic. Companies that have traditionally been stable see their business models challenged by algorithms and self-learning systems. In short: it is no longer an issue if AI will affect business, without how.
For today's business leaders, it is therefore a matter of understanding the technology in depth in order to be able to guide development — not just letting the IT department keep the wheel. Sure, AI's rampage may seem dizzying, but sticking your head in the sand is about as effective as ignoring the elephant in the server room. Business logic is changing at a supersonic pace, and far-sighted organizations are already preparing. This review comes at the right time—to provide a credible, strategic look at where AI is taking us next, without falling into the limp and with the twinkle in the eye.
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AI puts the business user in the driver's seat
Gone are the days when you needed to call the IT department for minimal data analysis. AI and user-friendly tools enable business users to solve problems themselves and realize ideas directly in the business. The phenomenon is sometimes referred to as “AI democratization” and involves opening up AI development to people without a deep technical background. With intuitive interfaces, pre-built models, and low-code platforms, a marketer or product manager can develop a prototype in days instead of months. The occasional tech specialist may raise an eyebrow at this shift in power (and perhaps take an extra sip of tea to keep calm), but the development is hard to ignore.
A recent global survey found that 75% of companies surveyed saw up to 50% shorter development times using AI and automation, and that more than half experienced higher quality with fewer errors.
As cloud services and open AI frameworks have become available, the threshold for innovation has also been lowered for smaller players. Companies that previously did not have the resources or skills to develop their own AI can now benefit from ready-made components — for example through cloud APIs or open source models — at fractions of the previous cost. That means innovation is no longer reserved for the tech giants; even a small startup or municipal administration can experiment with AI-driven ideas.
This is, of course, no “death” for the IT department, but a redefinition. Specialist knowledge is still needed to build robust infrastructure, ensure data quality and guide users in the right methodology. But the focus is shifting: IT becomes enabler and coach rather than bottleneck. In the long run, this shift of power lays the foundation for a culture where innovation happens continuously across the breadth of the organization — with business at the helm and technology as a loyal map reader.