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This study investigates the practical impact of organizational AI policies on software developers, revealing that strict regulations often hinder adoption if they lack developer-centric engagement. By analyzing 19 interviews, the research identifies specific friction points where risk mitigation measures inadvertently slow down development workflows or discourage legitimate LLM usage. The findings offer actionable guidance for managers aiming to balance security concerns with the operational realities of engineering teams.
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AI Policies: Help or Hindrance? A Software Developer's Perspective

arXiv1 min read

arXiv:2609.16496v1 Announce Type: cross Abstract: AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not useful if software developers do not engage with them. We draw on 19 software developer interviews to show how AI policies help and hinder developers. We suggest approaches to support managers and decision makers with a developer-centric approach to introducing AI policies.

Title:AI Policies: Help or Hindrance? A Software Developer's Perspective

Abstract:AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not useful if software developers do not engage with them. We draw on 19 software developer interviews to show how AI policies help and hinder developers. We suggest approaches to support managers and decision makers with a developer-centric approach to introducing AI policies.

Software Engineering (cs.SE); Artificial Intelligence (cs.AI)

arXiv:2609.16496 [cs.SE]

(or arXiv:2609.16496v1 [cs.SE] for this version)

https://doi.org/10.48550/arXiv.2609.16496 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 168 words

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