How mature is Switzerland in AI? Insights from the AI Maturity Study by ti&m and HSLU

While generative AI has been dominating the headlines since 2022, the extent to which companies in Switzerland have actually taken this technology on board remains to be seen. That is precisely where the AI Maturity Study by ti&m and HSLU comes in. Its aim was to provide a factbased assessment extending beyond a public perception that veers between euphoria and fear. While there is often debate in society about the risks – from job losses to threats to democracy – economic analyses show that AI holds enormous potential for productivity and prosperity in Switzerland.

The AI Maturity Study evaluates organizations along four interlinked dimensions:

1. AI strategy
How clear is AI’s part in the corporate strategy? Is there an overarching vision for its use?

2. AI governance and roles
How are responsibilities, guard rails, and decisionmaking processes defi ned to ensure AI is used safely and compliantly?

3. AI use and processes
To what extent are AI solutions productively integrated into processes, products, and decisionmaking? Can their benefi ts be measured?

4. AI skills and culture
What skills, learning formats, and values characterize the use of AI and promote an innovationfriendly attitude?

This structure combines methodical rigor with practical relevance: It is based on international frameworks such as those used by EY, BCG, and Gartner. It is also tailored to the specifi c circumstances of the Swiss economy, from data protection and regulation to the shortage of skilled workers and the strong SME base.

The study is still ongoing, but initial fi ndings present a consistent picture: Many companies recognize the strategic importance of AI, but only a few have the structures in place to use it systematically: 

• Around a third of those surveyed have formulated an explicit AI strategy 
• Half of them lack formal governance rules and roles 
• Fewer than 30 percent have AI solutions in productive use

Many organizations limit themselves to pilot projects, such as document or process automation, and have not yet made full use of the potential.

The differences between the sectors are clear:

Financial services providers are among the pioneers of the technology. However, they mainly use AI in specific, highly regulated processes such as risk analysis, fraud detection, or customer communication. Many projects are still being validated. Scaling often fails due to data and compliance hurdles.

Industrial companies particularly use AI in production, logistics, and quality assurance in order to increase efficiency and thus achieve faster value creation.

Public administration and the health sector are catching up. However, they struggle with heterogeneous data sources and a shortage of specialists.

An international comparison (BCG 2024, ETH/Swissmem 2024) puts Switzerland in the upper middle tier: technologically strong, strategically ambitious, but with some catching-up to do in terms of governance, data management, and culture.

A key finding of the survey to date is that businesses which define clear responsibilities and data standards achieve measurable progress more quickly. Without structured governance and a consistent database, AI is usually limited to the experimental stage. In regulated industries especially, the ability to use data securely and traceably is crucial to success.

At the same time, it is becoming clear that the debate about risks must not obscure the opportunities. AI does not replace workers in the physical sense. Rather, it re-lieves them of routine tasks without taking up living space, resources, or jobs. In a labor market suffering from acute shortages in many sectors such as healthcare, education, industry, and ICT as a result of demographic change, AI can help to alleviate bottlenecks and deploy resources with greater precision. That makes it part of the solution rather than the problem.

Technology is just the beginning: It is people who play the decisive role. International studies show that training, orientation, and trust are key factors for successful AI adoption. That is why the AI Maturity Study examines how businesses promote learning formats, experimentation, and ethical reflection. Organizations with an open learning culture and clear lines of communication use AI faster, more broadly, and more sustainably.

The AI Maturity Study will run until the beginning of 2026. It will then be published on the ti&m website. The results will reveal how far Swiss businesses are on the road to the systematic and responsible use of AI – and what levers they will have to pull in the future to move from pilot projects to sustainable value creation. Switzerland is facing a rare opportunity: AI can increase productivity, prosperity, and quality of life, provided it is used with boldness, has a structured form, and enjoys the confidence of society. Fear has nothing to teach us – but strategy does.

Studies cited and other sources

EY European AI Barometer (2025) shows how European businesses use AI strategically and where Switzerland stands in comparison.
ETH Zürich / Swissmem (2024) analyzes the use of AI in Swiss industry and identifies success factors for productivity and innovation.
BCG AI Maturity Matrix (2024) ranks countries worldwide according to their AI readiness and emphasizes the importance of data and talent.

More at: ey.com, swissmem.ch and bcg.com