Defining business requirements has traditionally involved a high degree of human effort and interaction by business analysts (BAs). With the introduction of AI-powered assistants like BA Genie, the work of BAs can be streamlined to improve efficiency and improve the accuracy of requirements definition, increasing speeds time to market and enabling BAs to focus more time and attention on strategic, differentiating activities.

In a typical SDLC, BAs act as intermediaries between business stakeholders and technology teams, ensuring that business needs are accurately captured and translated into specifications. They elicit detailed business requirements through various methods, such as interviews, workshops and data analysis. 

BAs then analyze, elaborate upon, and document these requirements, creating comprehensive artifacts such as epics, features, user stories, and test cases. This meticulous process ensures that all stakeholder needs are adequately captured, while providing a common understanding around which product development teams can organize.

Defining business requirements can therefore be a laborious task, and the potential for misunderstanding can be high, resulting in frequent back and forth with business stakeholders. In addition, the need to adhere to industry best practices for documenting requirements increases the effort and workload, and can often distract BAs from understanding and elaborating business needs.