AI in Switzerland: Implementation is now crucial.
by Ahmed Schallenberg
In many companies, AI has long been an everyday companion. Yet one crucial step is often missing: moving from isolated experiments to genuine value creation.
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In Swiss companies, the question is no longer whether artificial intelligence applications will be used, but how consistently they are applied. According to the Swiss AI Report 2025 by CorpIn, nearly half of the surveyed companies are already using AI in initial processes. However, many of them are merely experimenting. The use of generative tools remains stuck at the pilot stage and is often superficial. The problem isn’t the technology. What’s missing is direction. Clear KPIs are rare. The business case remains vague. And in many cases, resources and expertise are lacking to turn early approaches into robust solutions.
AI creates value — when used correctly.
The gap between ambition and reality is wide. According to an ETH analysis, only around 8% of small companies use AI. Among large companies, the figure is more than one-third. But even there, AI often remains isolated. Individual tools sit alongside existing processes instead of transforming them. Yet the benefits are clear: according to a labour market study by AXA, nearly half of the companies report higher efficiency when AI is used in a targeted way. Processes run faster. Decisions become more data‑driven. But the expected economic impact still fails to materialize. The global picture is the same: what’s missing is consistent integration. And that is precisely where the difference between experimentation and value creation emerges.
The next step: AI takes over processes.
The focus of Swiss companies is shifting as well. AI is moving away from simply assisting and toward driving automated workflows. The keyword is Agentic AI: AI systems plan tasks independently, make decisions, and control processes. In Switzerland, the topic is still in its early stages. Initial pilot projects are underway — from workflow automation and IT and service processes to specialized industry solutions. The first digital end‑to‑end processes are already being co‑managed by AI agents. The direction is clear: AI will increasingly become part of end‑to‑end processes. Those who enter early will gain a competitive advantage.
Without governance, AI becomes a risk.
As AI usage grows, so do the requirements. Many companies do not struggle with the technology itself, but with organizing it. Responsibilities are unclear. Data structures are inadequate. Added to this is regulatory complexity: Swiss and EU requirements must be met simultaneously. And many central questions remain unanswered: Who is accountable for AI‑driven decisions? How are results validated? Which data may be used? Trust therefore becomes the decisive factor — not merely as a compliance issue, but as the foundation for productive AI use and thus a clear competitive advantage.
Whether AI is used in a Swiss company ultimately depends on the value it generates. If it remains an experiment, its impact fades. A better approach is to work with concrete goals, relevant use cases, and measurable outcomes. AI must become part of daily work — part of existing processes. This requires clean data, clear responsibilities, and an infrastructure that supports these processes. Only then can AI increase efficiency and deliver real value.
Ahmed Schallenberg, Teamleader Business Development
Infrastructure becomes a bottleneck.
Many companies follow a cloud‑first strategy. This accelerates digitalization: better scalability, enhanced security, and predictable costs make the cloud an attractive option. AI services are already included. At the same time, new dependencies arise — and with them, new risks. Companies that want to use AI productively therefore need more than standard solutions. What’s required is a well‑designed architecture that remains flexible while still providing control. Hybrid models, for example, combine scalability with data control. They protect data and ensure data sovereignty. They form the foundation for scalable AI applications. The challenge lies in implementation. And this is precisely where many organizations reach their limits. They lack experience and resources — and often a partner who can bridge strategy and execution. Because the interface between architecture and operational implementation ultimately determines whether AI truly works within the company.
AI succeeds at the workplace.
Ultimately, success becomes visible where AI is actually used: in everyday work. Modern AI applications and solutions place significantly higher demands on hardware. Computing power, memory, and energy efficiency become limiting factors. Technology companies such as Lenovo are responding with business devices, infrastructure, and services specifically designed for such workloads — mobile, powerful, and equipped with dedicated AI processors: Neural Processing Units (NPUs). With local AI processing for greater data protection and with support for faster workflows through intelligent automation. This is what enables AI to be used directly at the workplace
Without an implementation partner, AI remains fragmented.
But technology alone is not enough for the successful use of AI. Companies need to identify use cases, adapt their infrastructure, and execute rollouts properly. This is exactly where integration and consulting partners come into play. Providers like Bechtle support companies throughout the entire process – from prioritization and introduction to ongoing operations. Even new approaches such as agentic AI can be integrated into business processes in a structured way. As a Lenovo Platinum Partner, Bechtle can leverage the appropriate technologies and scale projects effectively.
For companies, this means: With the support of partners like Bechtle, AI is not introduced as an isolated tool but developed as an integrated part of their working environment – from data to processes to hardware.
Competitive advantage depends on leading the way.
The development is clear: in the coming years, AI will become deeply integrated into business processes. The question is no longer whether Swiss companies will use AI, but how quickly they can move into real implementation. Those who take a structured approach to integrating AI into their processes now will gain efficiency, speed, and new opportunities. Those who continue to merely test will lose valuable time.
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This article was produced in collaboration with Netzwoche.