AI requirements engineering: precision over misdevelopment
Integrating AI into business processes not only makes value chains more efficient but also more complex. Traditional methods of requirements analysis often reach their limits here: AI systems behave probabilistically, rely on data rather than rigid rules, and demand new standards in terms of transparency and security. Treating AI projects like conventional software risks costly missteps, lack of acceptance, or legal hurdles regarding issues such as transparency, fairness, security, and traceability.
The key to success lies in modern, AI-specific requirements engineering (RE). It forms the foundation for bridging the gap between human needs, technical capabilities, and data-driven realities. Learn how to gather and document requirements with such precision that your AI systems are not only technologically stable but also generate genuine, ethically sound value for your business.
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- Specific AI expertise: you will learn how to define requirements for AI projects in such a way that critical aspects—such as transparency, fairness, and ethical principles—are integrated into the system architecture from the very beginning.
- Structured methodology: you will receive clear guidance on managing requirements in an AI-driven world, enabling you to communicate efficiently and in compliance with legal requirements with internal teams and external partners.
- Practical techniques: we teach you methods for structured documentation and show you how to use techniques such as prompting to make requirements for AI systems easier to understand.
- Future-proof quality assurance: you will learn how RE methods are evolving and how to ensure the long-term stability of your AI solutions through intelligent requirements management.
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The content is aimed at specialists and managers who develop, integrate, or oversee AI systems.
- Requirements engineers and systems engineers
- Software and AI developers
- Data scientists and machine learning engineers
- Product owners and project managers for AI systems
- Specialists and managers in digital transformation, IT, and innovation
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- Format: webinar / workshop / training
- Duration: flexible
- Delivery: online or in-person
- Practical component: high, with examples and specific application scenarios
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The format can be customized to suit your organization’s specific needs—for example, by:
- Incorporating your specific use cases
- Adapting to your industry or project type
- Delving deeper into specific methods or tools
