DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code

Pratyush Nidhi Sharma, Lauren Wright, Anne Herfurth, Munsif Sokiyna, Pratyaksh Nidhi Sharma +2 more
8/23/2025
cs.SEcs.AI

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Abstract

Generative AI coding assistants (ACAs) are widely adopted yet pose serious legal and compliance risks. ACAs can generate code governed by restrictive open-source licenses (e.g., GPL), potentially exposing companies to litigation or forced open-sourcing. Few developers are trained in these risks, and legal standards vary globally, especially with outsourcing. Our article introduces DevLicOps, a practical framework that helps IT leaders manage ACA-related licensing risks through governance, incident response, and informed tradeoffs. As ACA adoption grows and legal frameworks evolve, proactive license compliance is essential for responsible, risk-aware software development in the AI era.

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Cite this paper

@article{sharma2025devlicops,
  title  = {DevLicOps: A Framework for Mitigating Licensing Risks in AI-Generated Code},
  author = {Pratyush Nidhi Sharma and Lauren Wright and Anne Herfurth and Munsif Sokiyna and Pratyaksh Nidhi Sharma and Sethu Das and Mikko Siponen},
  year   = {2025},
  eprint = {2508.16853},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.16853v1}
}

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