AI in Requirements Engineering («AIRE»)

• Understanding AI: Basic knowledge of AI, its history and possible applications in requirements engineering
• Automating requirements analysis: Using AI to automate requirements analysis and prioritisation
• Improving quality assurance: Using AI to improve the quality and consistency of requirements
• Documenting efficiently: Using AI tools to automate documentation and requirements management
• Communicating with AI: Improving communication and collaboration in requirements management through the use of AI

1 Overview and Introduction Artificial Intelligence in Requirements Engineering 

• Definition and basics of AI
• Basics of effective prompting
• Applications and benefits of AI in requirements engineering

2 AI Tools and Technologies in Requirements Engineering 

• Overview of various AI tools and technologies that can be used in requirements engineering

3 AI use cases in Requirements Engineering 

• Use of AI in requirements elicitation and analysis
• Automated requirements documentation and management
• AI-based requirements quality assurance and validation
• Managing and prioritising requirements more efficiently with AI tools
• Improving communication and collaboration in requirements engineering with AI

4 Limitations, challenges and ethical aspects of AI in Requirements Engineering 

• Managing potential risks and limitations of AI in requirements engineering
• Privacy and data security when using AI
• Ethical considerations and responsibilities when using AI in requirements engineering

5 Outlook on the future of AI in Requirements Engineering 

• Trends and developments in AI in requirements engineering
• Potential and opportunities for future applications of AI in requirements engineering

Interactive and hands-on training

This training is aimed at:

• Requirements engineers: People who gather, analyse and document requirements will benefit from this training as it will show them how to use AI to improve their work.
• Business analysts and business engineers: This group can use the training to understand how AI tools can support their analysis and requirements.
• Product engineers: Engineers involved in the development of products learn how AI can optimise their requirements and development processes.
• Project employees: People working in project management who need to set, define or interpret requirements can benefit from the new possibilities offered by AI.
• System analysts and test managers: Anyone who specialises in testing will learn how to get efficient support when designing test cases and analysing the test coverage of AI tools.
• Software developers and project managers: Strengthen requirements management and project planning skills through the targeted use of AI tools.
• Quality managers and IT consultants: Expand understanding of the importance of requirements in quality assurance and use of AI tools to optimise these processes.

For successful participation in the training, a basic knowledge of requirements engineering is helpful to understand the use of AI methods in the right context. Basic knowledge of information technology and data analysis is also an advantage.

An essential prerequisite is the openness and willingness to engage with new technologies and concepts, and to integrate innovative approaches into everyday working life.