Switzerland invests in AI – but its path faces barriers

1. Adoption of AI tools is below the global average

Swiss organisations show strong interest in AI, particularly in strategic applications. Notably, 53% of Swiss respondents report using strategic AI tools, surpassing the global average of 48%, indicating a proactive approach to integrating AI into core business functions. But the overall adoption rate of AI tools across the workforce is somewhat conservative: 31% of Swiss companies report moderate or limited adoption (1-40% workforce usage), below the global average of 38%. This suggests that while leadership is keen on AI, broader employee engagement remains a challenge.

Interestingly, Switzerland ranks second out of fourteen countries in expecting AI initiatives to positively impact business models within 1-2 years, with 48% of respondents anticipating such effects—8 percentage points above the global average of 40%. Yet only 5% say AI has already transformed their business models, which is below the global average of 11%. This gap shows that optimism about the future potential of AI is tempered by a sense that AI’s impact on businesses so far remains limited.

Swiss AI use cases are concentrated in IT (33%) and Finance (17%), both above global averages. HR and Legal lag behind, with only 9% and 3% respectively reporting significant AI use cases. This uneven distribution shows the scope to expand AI’s reach within Swiss organisations.

Chart 1. To what extent, if at all, has your organisation adopted approved AI tools/applications?

2. Investment trends: confident yet calculated

Swiss enterprises exhibit robust financial commitment to AI. About 30% plan to increase AI investment significantly (+20% to +39%) over the next year, notably higher than the global average of 23%. Furthermore, 22% have already increased investment significantly in the past year. This reflects growing confidence in AI as a strategic asset.

The allocation of AI governance responsibilities also stands out. A remarkable 22% of Swiss organisations have designated the Chief Data Officer (CDO) as the primary AI leader, well above the global average of 14%. This centralised leadership model may facilitate focused strategy and accountability.

However, only 3 % have dedicated AI or innovation teams, slightly below the global average of 5%, indicating a preference for integrating AI leadership within existing structures rather than creating specialised units.

Chart 2. Compared to the previous 12 months (since August 2024), how has your organisation's financial investment in AI changed, if at all?

3. Expected returns and measurable impact: high aspirations, with some reservations

Swiss leaders are optimistic about returns on AI investments. A striking 52% expect measurable returns from generative AI within one year, significantly higher than the global average of 38%. The belief in a rapid ROI reflects their strategic priority which is to look for quick wins from AI.

Yet, enthusiasm for agentic AI—AI systems capable of autonomous decision-making—is more muted. Only 23% expect significant returns within a year, roughly aligned with global figures. This cautious stance may reflect uncertainties about agentic AI’s risks and complexities.

Swiss organisations report strong perceived benefits from AI in decision-making and governance, with 81% agreeing AI has improved these areas, closely matching the global average. However, improvements in product and service agility (77%) and customer engagement (73%) lag slightly behind the global figures, suggesting there is room to enhance AI’s role in market responsiveness and client relations.

Chart 3. When do you expect to see significant, measurable return on investment from your organisation’s implementation of Generative AI?

4. Workforce engagement and training: a critical gap

A notable challenge for adoption of AI in Switzerland is workforce readiness. Only 24% of Swiss organisations mandate AI training for employees, significantly below the global average of 37%. While 55% offer voluntary training—above the global average—the fact that this training is voluntary may hinder widespread adoption and proficiency.

The training gap is reflected in usage patterns: 27% of Swiss employees using AI tools engage with them less than once a week, the highest low engagement figure among all surveyed regions, and a similar percentage, 22% of Swiss employees use AI tools daily – this, too, was the lowest of all countries and compares to a global average of 36% of employees using AI tools daily. The primary barrier cited is a "lack of viable use cases" (35%), also well above the global average of 24%. This indicates that there is a need for clearer communication and demonstration of AI’s practical benefits to employees.

Concerns about AI’s impact on skills development and job satisfaction are relatively low in Switzerland, suggesting a generally positive workforce attitude toward AI, provided adequate support and guidance are available.

Chart 4. Business user AI training focuses on helping employees to understand how AI impacts business processes and how to work with AI tools or outputs. Which of the following statements best describes the AI training offered to employees in your organisation?

5. AI expertise and maturity: leading in generative AI experimentation

Swiss organisations lead in generative AI experimentation, with 37% engaged in ad-hoc or small team usage, surpassing the global average of 31%. However, deep integration or optimisation of generative AI remains limited, at 8%, barely half the global average of 17%.

Agentic AI expertise is aligned with global trends but remains less developed, reflecting the cautious approach noted earlier.

Chart 5. How would you describe your organisation's current level of overall expertise regarding Generative AI?

6. AI use cases across functions: strengths and opportunities

The survey reveals Swiss strengths in AI use cases within IT, Finance, and Cybersecurity, all above or aligned with global averages. Conversely, Manufacturing and Operations (12%) and Legal (15%) show lower AI engagement, highlighting potential growth areas.

Customer service and marketing AI use cases are slightly above global averages: Swiss companies recognise AI’s capacity to enhance customer interactions and improve brand positioning.

Chart 6. In which of the following functions do you have the greatest number of AI use cases currently? Please rank the top three.

7. Measuring ROI: a balanced and nuanced approach

Swiss organisations tend to use a variety of metrics to measure AI’s ROI, with a notable 38% differentiating between generative and agentic AI metrics, above the global average of 30%. This tailored approach reflects an understanding of AI’s diverse impacts.

Commonly used metrics include customer satisfaction (47%), time savings/productivity (45%), and risk reduction (40%), all of which are above global averages. However, AI’s revenue uplift and cost savings are measured slightly less frequently, suggesting a focus on operational and experiential benefits over direct financial gains.

Chart 7. How often are the following metrics used when you measure the return on investment on the AI use cases your organisation implements? With answer "most of the time."

8. Barriers to ROI: talent, and use case identification

The top barriers to achieving AI ROI in Switzerland are a lack of technical talent and skills (30%) and difficulty identifying use cases (27%), with a slightly higher score for use case identification than the global average.

Cultural resistance (23%) and over-reliance on external vendors (26%) are also a little above the global average levels, indicating the importance of building internal capabilities and change management.

Chart 8. Which barriers, if any, are preventing your organisation from achieving a return on investment (ROI) from its AI initiatives? Please select all that apply.

9. AI’s contribution to innovation: leadership in product improvement

Swiss organisations report AI’s greatest innovation contributions in product improvement (57%), service improvement (46%), and process transformation (40%). The product improvement figure is significantly higher than the global average of 41% and shows that Swiss companies are focusing on enhancing offerings through AI.

But AI’s role in enhancing customer experiences (37%) and new service development (38%) is slightly below global averages, suggesting potential areas for strategic emphasis.

Chart 9. To what extent, if at all, has AI contributed to innovation in your organisation in the following areas? With answer "to a great extent."

10. The outlook: Swiss AI use is promising but requires focused efforts

Swiss enterprises are optimistic about AI’s transformative potential, with strong investment plans and expectations for rapid ROI, especially in generative AI. But lags in workforce training, use case identification and broader AI adoption temper this optimism.

To fully capitalise on AI, Swiss organisations should:

• Expand AI training: Move from voluntary to mandatory programmes to boost employee engagement and proficiency.
• Broaden AI use cases: Especially in underrepresented functions like HR, Legal, and Manufacturing.
• Enhance cultural readiness: Address resistance through leadership commitment and clear communication.
• Balance efficiency and revenue focus: While operational gains are strong, more emphasis on revenue growth opportunities is needed.
• Develop agentic AI expertise: Prepare for longer-term transformative AI applications with appropriate governance and risk management.

Conclusion

Switzerland’s AI landscape is characterised by strategic enthusiasm, solid investment, and a strong focus on generative AI. Compared to global peers, Swiss organisations are confident about AI’s near-term impact on business models and returns. However, full integration of AI is being hindered by limited workforce engagement and the need to develop a wider range of use cases.

By addressing these challenges with targeted training, cultural alignment, and strategic expansion of AI applications, Swiss enterprises can unlock AI’s full potential, securing a competitive edge in the evolving digital economy.

Methodology

From 15 August to 5 September 2025, Deloitte surveyed 1,854 senior executives in Belgium, Denmark, France, Germany, Ireland, Italy, Norway, Poland, the Kingdom of Saudi Arabia, Sweden, Switzerland, the Netherlands, the United Arab Emirates and the United Kingdom. 99 respondents from Switzerland participated.

All organisations have one or more working implementations of AI in daily use. Additionally, they have pilots in place to explore generative AI, or have one or more working implementations of generative AI in daily use.

Respondents meet one of the following criteria with respect to their organisation’s AI and data science strategy, investments, implementation approach and value measurement: they influence decision-making, are part of a team that makes decisions, are the final decision-maker, or manage or oversee AI technology implementations.

Twenty-four interviews were conducted with executives in France, Germany, the Netherlands and the United Kingdom, with six interviews in each country. Deloitte's internal generative AI platform was used to significantly accelerate the analysis of interview transcripts, reducing processing time from weeks to hours while maintaining a rigorous and methodological human-led approach.