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In this last part of this blog series, I will talk about integrating AI into the software development lifecycle and provide a strategic framework for Software Companies.

At the end of my master thesis I proposed an AI-Augmented framework on how to effectively integrate artificial intelligence (AI) within the New Software Product Development (NSPD) lifecycle. While the NSPD life-cycle primarily focuses on new software product development, its various stages can be seamlessly incorporated into specific processes used by software companies.

AI-Augmented New Software Product Development Framework

Figure 1 shows how AI can be strategically integrated at each stage of the NSPD life-cycle.

Figure 1. AI-Augmented New Software Product Development Framework

1. Analysis Phase: AI tools can streamline tasks such as competitor analysis and market summaries. AI can be used to gather user requirements through AI personas. These personas will provide more accurate insights into user needs and market demands.
2. Planning Phase: In this stage, AI facilitates rapid prototyping and helps experiment with various technological choices. This enables companies to gather customer feedback more quickly, leading to more informed decision-making and quicker adjustments in development strategies.
3. Development Phase: By integrating AI within Integrated Development Environments (IDEs), teams can enhance productivity. AI can assist with tasks such as unit testing and documentation, making the development process more efficient.
4. Deployment Phase: Automation powered by AI can streamline multiple tasks, such as creating customer documentation and detecting security vulnerabilities. This not only improves efficiency but also enhances customer satisfaction.
5. Maintenance Phase: AI can play a crucial role in ongoing support tasks. For instance, managing customer interactions through AI chat-bots and analyzing log files for early warning systems and software bug detection. These capabilities significantly boost system reliability and user satisfaction.

Conclusion

AI-Augmented New Software Product Development Framework provides a strong starting point for software companies to integrate AI into their workflows. In the end, by strategically applying AI technologies throughout the software development life-cycle, software companies can enhance their workflows, improve decision-making, and ultimately achieve greater efficiency and success in their product development processes. This structured approach ensures that businesses are well-equipped to navigate the complexities of modern software development while leveraging the transformative power of AI.

Sources:

Arman, M. N. (2025) ‘Join New Software Product Development with Artificial Intelligence: Investigation of Useful Factors of AI Integration in Software Development’