How AI can revolutionize requirements evaluation

In the past year, artificial intelligence has surged into the spotlight, becoming a prominent topic on our agendas. It’s not just a buzzword anymore – natural language-based models are making AI available to everyone at a disruptive pace. Not only does this revolutionize the way we work, it also represents a turning point for software. It is therefore all the more important to embrace this development and harness the potential that using AI brings to our daily work — especially in areas like requirements management, where manual and repetitive tasks slow down processes. Let’s specifically look at how AI supports users in tackling challenges in requirements evaluation and how it can help to solve them in Polarion ALM.

Complex requirements, less time

Managing requirements is a critical and time-sensitive process. When suppliers receive new specifications from their customers, the pressure is on to respond quickly and efficiently to stay competitive. However, this is easier said than done. Engineers must read, check, and evaluate a large number of stakeholder needs and customer requirements manually. Even though the content is only slightly different from previously reviewed specifications. The key challenges can be summarized as follows: 

• Extensive effort: Manually reviewing and linking requirements is, above all, repetitive work that requires a lot of effort and is very time consuming.
• Time pressure: While the time to respond to the customer is getting shorter, requirements are becoming more complex.
• Risk of human error: Humans are not machines. Tasks such as requirements analysis are particularly prone to error.
• Lack of experienced professionals: The expertise needed for evaluation is often solely located in the heads of experts, who are becoming scarcer for demographic reasons.

Faced with these challenges, it’s obvious that handling requirements without automation is no longer an option.

Knowledge-driven requirements analysis with AI

At first glance, there is a logical explanation for processing new stakeholder needs and customer requirements in manual steps: They are usually worded differently, which makes automation difficult. However, this is exactly where AI can unfold its full potential. Adaptive AI, utilizing technologies such as Large Language Models (LLMs), can read and understand large amounts of text – regardless of wording or language. Without training or expensive fine-tuning, it is possible to quickly compare and analyze any kind of stakeholder needs or requirements on a semantic level. What would take a requirements engineer several hours to accomplish, AI can do in seconds.

In practice, this leads to a highly valuable use case: There is an enormous amount of knowledge from previous requirements projects. It’s like a treasure chest of valuable insights that just wants to be unlocked with the help of AI. These insights can serve as a foundation for evaluating new stakeholder needs and requirements. By transferring the data to Polarion ALM via AI, users can automatically compare new requirements on a semantic level with previously evaluated ones and receive a list of matching requirements – along with all related information and references. This provides users with a shortcut for evaluating requirements and updating their attributes and links with just a few clicks, all while maintaining full control over their analysis results.

Polarion ALM and AI – a powerful synergy

While Polarion ALM offers a comprehensive solution for managing the entire requirements lifecycle with full traceability, AI can be seamlessly integrated as an extension. This allows users to leverage AI capabilities within their familiar working environment and adhere to common workflows. The fact is, incorporating AI-driven features not only enhances the quality of the requirements management process but also improves decision-making and collaboration among project stakeholders.

Evaluating stakeholder needs with an AI boost is just the beginning. With the help of LLMs, it will be possible to support many other process steps throughout the lifecycle in the near future, such as requirements or software code generation and quality checks. Close cooperation between customers and partners is needed in order to discover further features and thus drive forward the development of modern AI-driven requirements management.
Do you want to learn more about how Polarion ALM and their partner thingsTHINKING are solving the challenges in requirements management using AI? Check out the semantha extension in Polarion’s extension portal or visit the following website: https://www.semantha.de/polarion/