Swiss SMEs and artificial intelligence: utilising opportunities, mastering challenges
Many companies are faced with the question of how they can use AI sensibly and overcome challenges such as costs, data protection and a lack of expertise. Our new practical guide provides practical solutions.
AI tools such as ChatGPT or DeepL are already in use in Swiss SMEs, but often lack a clear strategy. Many companies are struggling with uncertainties regarding integration and the associated investments. At the same time, the pressure to remain technologically competitive is increasing.
Our new practical guide shows where AI offers the greatest added value and provides concrete solutions for typical hurdles such as high costs, a lack of expertise or regulatory requirements.
In addition to the guide, SAIROP (Swiss Artificial Intelligence Research Overview Platform) provides you with a comprehensive overview of services that support companies in taking the next step in the field of artificial intelligence.
Key findings from the practical guide:
Opportunities for SMEs through AI
- Increased efficiency through process automation
- Better decision-making through data-based analysis
- New business models and market potential
- Increased competitiveness
Challenges and solutions
- Lack of expertise: further training and external advice are key
- High costs: funding programmes and partnerships facilitate access
- Data protection and compliance: clear guidelines and a secure infrastructure build trust
- AI as a ‘black box’: increasing transparency and managing risks
Important applications for Swiss SMEs
- Content creation with AI – texts, translations and style optimisation with Microsoft Copilot
- Image and video analysis – automated quality control and document processing
- AI in software development – code analysis and error detection with tools like Gemini
- AI-supported decision-making – better forecasts and data-driven planning
- Optimisation in production and logistics – more efficient supply chains and inventory management
- Predictive maintenance – early detection of machine problems to avoid breakdowns