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AI Management
How to protect your company's data?
Artificial intelligence (AI), and more specifically generative models such as ChatGPT, offer considerable opportunities for businesses in terms of productivity, innovation and decision-making. It has become an essential tool in many business
sectors.
However, the use of AI raises new questions, particularly in relation to the models used and in connection with data protection, intellectual property and security. We follow the constant developments in this field at European and Swiss level.
How can data confidentiality be guaranteed when employees use AI tools to work? What are the risks involved? And how can companies using AI be protected?
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Switzerland is a pioneer in the field of AI. In the healthcare sector, algorithms are already analyzing medical images to help doctors make accurate diagnoses. AI is also accelerating the discovery of new drugs. In finance, it optimizes stock market transactions and detects fraud. In industry, it predicts machine breakdowns and improves quality control. In e-commerce, chatbots respond to customers and algorithms offer personalized recommendations.
Artificial intelligence represents a tremendous growth driver for Swiss companies. By automating repetitive tasks and optimizing processes, it can also significantly improve operational efficiency.
The adoption of AI by Swiss SMEs, while exciting, is held back by several specific challenges:
On the one hand, regulatory constraints, in particular the European AI Act, provide a strict framework for the use of AI in Europe, and may frighten Swiss companies. In Switzerland, as we have no equivalent to the European text, the provisions of laws such as the Federal Act on Data Protection (FADP) are applicable. These standards are scattered throughout the Swiss legal system, and can be particularly rigorous in sensitive sectors such as healthcare or public services.
On the other hand, the limited resources of SMEs, both in financial terms and in technical skills, are a major obstacle to a careful evaluation of complex AI solutions.
Training AI models requires huge amounts of data. This must be done in compliance with current data protection standards. In addition, the choice of training data used must ensure that biases generating discriminatory results are not introduced. Finally, the models themselves may be vulnerable to cyber-attacks, exposing companies to the risk of breaches of data security (accidental or unlawful data loss).
Finally, the use of AI raises complex legal issues, particularly in terms of intellectual property, as the data used to train models may be protected by specific rights.
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Assess your needs: Clearly define the goals you want to achieve with AI.
Choose the right tools: Opt for reliable, secure solutions from suppliers who meet the highest security standards.
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Include a human: Ensure that a human can intervene in an automated process by acting as supervisor, moderator or validator.
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Train your staff: Make your teams aware of the risks involved in using AI and the best practices to adopt.
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Integrate AI into your information security policy: Draw up a clear and precise policy defining the rules to be respected when using AI.
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Protect your data: Implement technical and organizational measures to protect your data (encryption, restricted access, etc.) based on a data protection impact analysis (concrete risk analysis)
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Monitor activities: Set up a monitoring system to detect anomalies and security incidents.
Our advice: Consider artificial intelligence as a long-term investment. Do your due diligence in evaluating projects before releasing the resources needed to carry them out.
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