With its ability to analyze data and quickly generate new content, generative AI offers Swiss SMEs an unprecedented boost in productivity. However, its smart and responsible use requires careful consideration of ethical and legal aspects.
The launch of ChatGPT by OpenAI in November 2022 marked the beginning of one of the most significant technological breakthroughs of the decade: generative artificial intelligence (AI). Capable of creating text, images, music, and even videos, generative AI systems have rapidly gained traction in businesses worldwide, including in Switzerland. According to a 2024 study by the consulting firm Implement, Switzerland could see an 11% increase in its gross domestic product (GDP) over the next decade, driven by the productivity gains these new tools enable.
AI vs. generative AI
Traditional artificial intelligence (AI) models analyze existing data based on predefined rules or algorithms, primarily performing tasks such as classification, prediction, or problem-solving. In contrast, generative AI systems – such as ChatGPT, Microsoft Copilot, Google Gemini, Perplexity AI, Claude, Neuroflash, DALL·E, Midjourney, Murf, and Tome – learn from data to create entirely new content, including text, audio, images, and videos. In many ways, these tools emulate the way the human brain functions.
More information on AI here: Opportunities of artificial intelligence
Boosting productivity
From marketing content creation and enhancing customer experience through chatbots to developing new product prototypes and optimizing business processes, generative AI is a powerful driver of efficiency and productivity for businesses. It enables access to a vast range of ideas in record time, without requiring technical expertise.
The diverse applications of this technology help businesses across all industries save significant resources and costs while freeing up time for high-value tasks. Today, more than a third of Swiss SMEs use generative AI tools to write advertising copy, while nearly a quarter leverage them to create images, illustrations, or design elements for their clients. A 2024 study by the Sotomo Institute for insurer Axa, conducted among 300 companies, revealed these trends. In the pharmaceutical industry, some AI systems can even generate new protein sequences, accelerating drug discovery.
Moreover, according to a study by the Institute of Enterprise and consulting firm McKinsey, generative AI serves as a catalyst for transformation. The ideas generated by these tools drive continuous innovation and enable businesses to develop tailored solutions for their target markets. This, in turn, strengthens their competitive positioning in the industry.
Ethical and legal considerations
While generative AI tools are powerful, they also come with limitations that businesses must understand to ensure their responsible and effective use. These systems can produce highly convincing false information (deepfakes) and may reinforce biases or prejudices, which can be particularly problematic in areas like recruitment. They also pose risks related to data privacy, security, and quality control. Additionally, some AI-generated content may include copyrighted material, potentially leading to civil or even criminal liability.
To minimize these risks, companies must implement rigorous verification and validation processes and ensure that the AI tools they use comply with existing data protection regulations.
Practical implementation
Adopting new generative AI tools may seem like a significant challenge for companies with limited resources. However, many generative AI systems – such as ChatGPT (by OpenAI), Gemini (by Google), Claude (by Anthropic), and Perplexity – are readily available as "plug-and-play" solutions, requiring no major investment in new infrastructure or specialized expertise.
To ensure a seamless integration, businesses must also focus on employee adoption of AI. Companies that invest not only in acquiring AI tools but also in training their workforce to develop AI-related skills will gain a competitive advantage. According to the 2024 Work Trend Index published by Microsoft and LinkedIn on AI adoption in the workplace, such investments lead to more efficient, engaged, and inclusive teams.
For more
"Generative AI For Dummies", Pam Baker (2024), Wiley.
"Generative AI and Multifactor Productivity in Business", Bryan Christiansen, Festus Fatai Adedoyin (2024), IGI Global.
"Generative AI Business Applications – An Executive Guide with Real-Life Examples and Case Studies", David E. Sweenor, Yves Mulkers (2024), TinyTechMedia LLC.
