Artificial intelligence in software development
Pro Research Analysisby 
Searched over 200M research papers
Artificial Intelligence in Software Development: Key Applications and Benefits
Artificial intelligence (AI) is rapidly transforming software development by automating tasks, improving efficiency, and enhancing software quality. AI tools now support nearly every phase of the software development lifecycle, from requirements gathering to deployment, and are reshaping both engineering and management practices within the field Armyanova2023Anitha2025Sokolov2024.
AI-Driven Automation and Efficiency in Software Engineering
AI technologies streamline software development by automating repetitive and manual tasks, such as code generation, testing, and bug detection. This automation reduces development time, minimizes errors, and allows teams to focus on more complex and creative aspects of software engineering Armyanova2023Anitha2025Anupriya2024+1 MORE. AI-powered tools can generate code, suggest improvements, and even create prototypes, making the development process faster and more efficient compared to traditional methods Anupriya2024Sokolov2024.
Enhancing Software Quality and Testing with AI
AI significantly improves software testing by making it faster and more accurate. Machine learning algorithms can identify patterns in code, predict potential bugs, and automate test case generation, leading to higher software quality and reduced risk of defects Armyanova2023Anitha2025Sofian2022+1 MORE. AI also supports continuous integration and deployment by monitoring code changes and ensuring that new updates do not introduce errors Anitha2025Sokolov2024.
AI Applications Across Software Development Phases
AI is applied throughout the software development lifecycle, including requirements management, design, coding, testing, documentation, and deployment Armyanova2023Anitha2025Sofian2022+1 MORE. In management, AI assists with project planning, risk management, and team formation, while in engineering, it helps with creating prototypes, generating documentation, and supporting decision-making . AI can act as an executor, co-author, or consultant, depending on the task and integration level Sokolov2024Feldt2018.
Security and Risk Management with AI
AI technologies are increasingly used to enhance software security. For example, agent-based systems and neural networks can detect and prevent cyber threats, improving the speed and accuracy of network security monitoring . However, the use of AI also introduces new risks, such as the potential for insufficiently detailed documentation, complex software artifacts, and errors in AI-generated code. Ongoing quality control and adherence to corporate standards are essential to mitigate these risks Sokolov2024Feldt2018.
Challenges and Considerations in AI-Driven Software Development
While AI offers many benefits, it also presents unique challenges. Developing AI and machine learning systems requires specialized engineering practices that differ from traditional software development . Integration issues, ethical considerations, and the need for continuous professional development are important factors to address for successful AI adoption Anitha2025Silva2024Ramalingam2023. Taxonomies and frameworks, such as the AI-SEAL taxonomy, help organizations classify AI applications and understand associated risks, guiding strategic decision-making .
Conclusion
AI is revolutionizing software development by automating tasks, improving efficiency, and enhancing software quality across all phases of the development lifecycle. While the benefits are substantial, organizations must carefully manage the risks and challenges associated with AI integration, ensuring ongoing quality control and professional development to fully realize AI’s potential in software engineering Armyanova2023Anitha2025Silva2024+6 MORE.
Sources and full results
Most relevant research papers on this topic
DOI
DOI
DOI