AI use in Switzerland: between efficiency gains and the value creation gap

A recent survey of Swiss companies and public sector organizations is providing, for the first time, a comprehensive picture of how AI is adopted across industries and company sizes. Companies were surveyed via an online questionnaire on the following AI topics: strategy, governance, application, value creation, risks, competencies, and culture. About 200 companies from more than 15 industries participated in the study. At 22 percent, banking and financial services companies are the most heavily represented, followed by 14 percent in public administration, 9 percent in technology, and 8 percent in insurance. A quarter of the study participants have more than 2,500 employees, while small and medium-sized enterprises (SMEs) with up to 500 employees account for just over half of the participants. The study’s findings show that AI applications are currently used primarily in areas with relatively low technical and organizational barriers. These include, in particular, marketing, communications, and customer service. These applications are generally easy to implement and involve manageable risks; as a result, they are often used as a starting point for adopting AI. In contrast, the level of penetration in key valueadded areas such as production, logistics, and financial processes is much lower. In this context, the use of AI requires integration into existing systems and the adaptation of established processes, which is more complex.

The study also shows that the benefits of AI applications currently lie mostly in efficiency gains. In some processes, these can be significant, amounting to as much as 50 percent. In contrast, direct contributions to revenue growth have been rare so far. The use of AI is therefore primarily supportive rather than transformative. There is a clear correlation between level of investment and efficiency gains achieved, with higher levels of investment tending to yield greater results. It is less surprising to learn that large companies (with more than 2,500 employees) are more advanced in this regard than small and medium-sized enterprises. However, this also presents an opportunity for SMEs: With focused use cases and clear prioritization, they can achieve results faster than large organizations with more complex structures.

Most of the companies surveyed are currently investing a relatively small portion of their IT budget in AI. That said, about three-quarters of companies are planning to ramp up these investments in the coming years. This trend suggests that they are recognizing the strategic importance of AI. At the same time, the study shows that many companies are struggling to make the transition from individual use cases to widespread, productive use. A look into the future shows that companies are planning to implement AI technologies across virtually all business areas over the next three to five years. The expected increase in use cases is particularly pronounced in the areas of controlling/finance, HR/recruiting, logistics, and IT/cybersecurity.

• Start small, but don’t just wing it
• Anchor AI strategically before scaling up
• Define governance and manage risks
• Invest in skills through targeted continuing education
• Use external partners to build speed

Three Questions for Pascal Wild, Head of Business Innovation & Development, ti&m

Many companies are experimenting with AI but are only investing a small portion of their IT budget. How can they still create impact?
It’s not the size of the budget that matters, but having a real focus. Companies that use AI broadly but without a clear goal rarely achieve lasting benefits. Successful companies focus on a few use cases with a clear business impact. They also establish the necessary data and governance framework. Most importantly, they integrate AI methodically into their processes. Particularly when it comes to generative AI, solutions must draw on reliable internal sources of knowledge. Companies need to measure the quality of these sources systematically. Otherwise, all these AI solutions can deliver is good demonstrations.

Where do you currently see the greatest opportunities for Swiss companies engaging with AI?
Many companies underestimate their own potential. Switzerland boasts strong domain expertise, established processes, and high quality standards. Systematically combining this expertise with AI can generate tangible competitive advantages, such as automated decision-making, AI-powered customer interactions, or more efficient back-office processes. The greatest opportunity lies in making this knowledge usable in a structured way. At the same time, companies must ensure trust through clear governance and compliance.

What specific steps should companies take now? And how does ti&m help with that?
Speed is what counts now. The most important step is to move from pilot projects to productive implementation. Many companies have been testing AI, but only a few are already achieving a real impact with it. This is exactly where we come in: We identify prioritized use cases with clear business value. We make sure that the necessary data, security, and governance frameworks are in place. And most importantly, we integrate AI into day-to-day operations. It is not the technology alone that matters, but how AI interacts with processes, data, and expertise. This is how organizations create lasting impact.