AI/ML for continuous feedback
Implementing continuous feedback involves systematically gathering, analyzing, and acting on feedback from users and stakeholders throughout the development, delivery, and production life cycle. This process is designed to enhance the software’s reliability and the team’s responsiveness to changes. Figure 8.8 illustrates activities essential for continuous feedback.
Figure 8.8 – AI/ML for continuous feedback activities
Potential bottlenecks and AI/ML solutions to address these challenges are explained in the following list:
- Feedback collection:
- Description: Gathering feedback from various sources, including user surveys, support tickets, and social media.
- Bottlenecks: The volume and variety of feedback can overwhelm manual processing efforts, leading to slow response times.
- AI/ML application: NLP and sentiment analysis can automatically categorize and prioritize feedback, helping teams quickly identify...
