By Adrian Giger (ERNI Switzerland)
Artificial intelligence is changing how we analyse, document and communicate requirements. From automating documentation to visualising data or supporting agile workflows – AI can help business analysts and requirements engineers save time, improve consistency and focus on what really matters: understanding business needs.
Understanding AI in context
Artificial intelligence has evolved from a buzzword to a fundamental force shaping how organisations design, analyse and deliver digital solutions. Far beyond simple automation, AI now enables systems to learn from data, interpret context, and support informed decision-making.
For business analysts (BAs) and requirements engineers (REs), AI can be a valuable assistant. Used thoughtfully, it helps save time, improve quality and provide deeper insights – without replacing the human expertise that remains essential to understanding complex business needs.
Where AI tools can add value
AI tools can make a real difference in many parts of a BA’s or RE’s work. Here are some of the most promising areas:
- Requirements analysis
Use AI-assisted tools to detect trends and patterns in requirements data. They can help identify redundancies or inconsistencies early in the process. - Text and feedback analysis
Natural Language Processing (NLP) can help analyse user feedback, surveys or interviews, highlighting recurring themes or problem areas. - Prototyping and mock-ups
AI-powered design tools allow quick creation of wireframes or mock-ups based on user requirements, enabling faster iterations and more focused feedback. - Automated documentation
Automating parts of documentation – such as specifications or requirements catalogues – saves time and ensures consistency. - Data visualisation
AI-driven tools can turn complex data into clear, intuitive visualisations, making it easier to communicate insights to stakeholders. - Risk analysis
AI can identify potential risks by analysing historical data and predicting where issues might occur. - Stakeholder management
AI can analyse communication patterns to identify key stakeholders or groups critical to project success. - Agile support
In agile environments, AI tools can help prioritise user stories, monitor sprint progress and predict delivery risks. - Requirements gathering via chatbots
Chatbots can capture initial user input or requirements before deeper interviews take place. - Learning and upskilling
AI-driven learning platforms offer personalised training paths and help BAs and REs stay current on new trends and technologies.
Making AI work for you
Like any tool, AI is most effective when used with purpose. Here are some tips for using AI wisely and efficiently:
- Define clear goals: Identify which tasks you want to automate or which problems you aim to solve.
- Do your research: Explore available AI tools to find which best fit your needs.
- Ensure data quality: Clean, well-structured data produces more accurate results.
- Test and adapt: Experiment with different tools and fine-tune them for your workflows.
- Integrate thoughtfully: Consider how AI fits into existing processes.
- Invest in training: Learn how to use the tools effectively; many offer tutorials or certifications.
- Stay ethical: Handle sensitive data responsibly and be transparent about the use of AI.
- Gather feedback: Continuously refine how AI supports your work.
- Keep learning: The field is evolving rapidly; staying informed ensures long-term value.
When AI tools make less sense
While AI offers many benefits, it’s not always the best solution. Consider avoiding or limiting AI use in situations such as:
- Small projects: When the effort to set up AI tools outweighs the potential benefit.
- Unclear or changing requirements: AI depends on structured input; unstable requirements reduce its effectiveness.
- Limited or poor data: Without sufficient data, AI results can be unreliable.
- Highly specialised domains: Deep domain expertise may be hard for AI to replicate.
- High-interaction environments: Human empathy and understanding are irreplaceable in stakeholder-heavy contexts.
- Strictly regulated industries: AI tools can add complexity to compliance processes.
In these cases, traditional methods guided by human judgment and communication remain the more pragmatic choice.
The bottom line
AI tools can significantly support business analysts and requirements engineers in their daily work – particularly in areas such as requirements analysis, documentation, data visualisation and risk assessment. However, not every situation benefits equally.
The key is balance: understanding when AI brings real value and when a human-led approach remains more efficient. As the technology continues to evolve, its potential will only grow. For BAs and REs, that means one thing – the role will stay exciting, dynamic and full of opportunity.
How is AI transforming other roles and are they even changing? Discover in one of our previous articles dedicated to the topics; AI is evolving work – but are our roles really changing?