In Switzerland, lagging adoption is holding back SME growth

In many Swiss companies, artificial intelligence arouses both enthusiasm and doubts. Managers know that it can improve productivity, but on the ground, integration often remains laborious. The tools are there… but habits don’t change.

The problem is that, in the absence of structured support and training dedicated to artificial intelligence, employees test AI from time to time and then quickly revert to their usual methods, because they don’t know how to embed it in their day-to-day tasks. This fragmented approach leaves much of the potential untapped.

Largely under-exploited potential

In 2024, an ETH/Swissmem study shows that few organisations go beyond pilots and only ~25% have an AI strategy. As a result, potential productivity is not being captured, and gains remain one-off rather than being embedded in processes.

On the SME side, recent barometers confirm that use is still tentative: 9% declare systematic use, 54% are in the testing phase, and many remain cautious compared with other European countries. In other words, the lack of a framework (data, governance, skills) is holding back the industrialisation of use cases.

Key statistics – Adoption of AI in Switzerland

• ~25% of Swiss companies have an AI strategy (ETH/Swissmem 2024).
• 54% of SMEs are still in the testing phase.
• only 9% are using AI systematically.
• Most advanced sectors: finance, ICT and manufacturing.
• Main obstacles cited: lack of internal skills, data governance, budget.

What it costs SMEs in practical terms

• Sub-optimal productivity: repetitive tasks not automated, longer time-to-market.
• Margin and competitiveness: higher operational costs in the face of competitors who are industrialising AI.
• Human capital: employees use AI “under the radar” without a quality/risk framework, hence variability in results.

In Geneva, the ecosystem is getting organised

Locally, Geneva is on the move: the Forum Économie Numérique – Impact de l’AI dans les PME (OCEI with FER Genève, HEG/HES-SO, OPI, Alp ICT) aims precisely at structured adoption (process, change, competitiveness).

From theory to real integration

When properly integrated, AI can transform everyday life.

• In marketing, it facilitates the creation of campaigns and visuals while respecting the brand charter.
• In human resources, it helps to write job offers, quickly analyse CVs or prepare relevant questions for an interview.
• In customer relations, it allows you to prepare personalised responses based on the history of exchanges.
• In management, it is used to analyse a market, model forecasts or compare different strategic scenarios.

What differentiates organisations that successfully leverage AI is how they integrate these practices into their existing processes. Good training does more than just show how to use a tool: it helps to rethink workflows, define a clear framework for use and establish new reflexes. It also reassures teams about the reliability of the results and shows them how to evaluate the answers obtained, rather than accepting or rejecting them indiscriminately.

The key role of leaders, managers and HR

They are the ones who provide the impetus, set the vision and create an environment where AI can really take root in practice.

• Managers: show that AI is not a fad but a strategic focus, integrate it into priorities.
• Managers: translate this vision into concrete actions, encourage experimentation and value success stories.
• HR: adapt training programmes, integrate new skills into objectives and performance indicators.

How we’re integrating AI at Procab

At Procab, we apply this philosophy to our own working methods. Integrating AI has already transformed several of our internal processes: automating certain production stages, generating optimised content more quickly, analysing data in real time, and improving project monitoring. We’ve seen an increase in responsiveness and quality that directly benefits our customers.

This experience enables us to support companies in their own adoption of AI, whether that means rethinking their workflows, integrating intelligent assistants into existing tools or designing new websites that are designed to exploit AI as soon as they go online.

Moving from experimentation to sustainable adoption

In French-speaking Switzerland, most start-ups begin with small, isolated experiments. But the real value emerges when these initiatives are linked into a coherent strategy, supported by a gradual build-up of skills.

This is where specialist support makes the difference: it transforms theoretical interest into real adoption, by adapting to the sector, the tools already in place and the company’s objectives.

Investing in AI today is not just about following a technological trend. It means preparing your teams to work more efficiently, innovate faster and remain competitive in a constantly changing environment.