Abstract
As generative AI technologies become increasingly integrated into software products, organizations face unique challenges in determining release-readiness. This paper presents a state-of-the-practice checklist derived from gray literature analysis, providing practitioners with a structured framework for evaluating generative AI-based software products before deployment.
Publication Details
- Journal: IEEE Software
- Volume: 42, Issue 1
- Pages: 74-83
- Publisher: IEEE Computer Society
- Year: 2025
Key Contributions
- Comprehensive survey of industry practices for generative AI release assessment
- Structured release-readiness checklist for practitioners
- Analysis of key considerations unique to generative AI systems
- Practical guidelines for quality assurance and risk management
Research Methodology
This study employed a systematic gray literature survey methodology, analyzing industry reports, blog posts, technical documentation, and practitioner guidelines to extract common practices and recommendations for releasing generative AI-based software products.
Citation
@article{patel2025state,
title={A state-of-the-practice release-readiness checklist for generative AI-based software products: A gray literature survey},
author={Patel, Harsh and Boucher, Dominique and Fallahzadeh, Emad and Hassan, Ahmed E and Adams, Bram},
journal={IEEE Software},
volume={42},
number={01},
pages={74--83},
year={2025},
publisher={IEEE Computer Society}
}