# LLM Company Policies and Policy Implications in Software Organizations

arXiv: https://arxiv.org/abs/2510.06718 · HTML: https://mlsanity.com/paper/2510.06718/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 6 references that are in the map.
- First posted on arXiv 8 Oct 2025.

## Builds on (most cited first, 4 of 4)

- [Automatic Programming: Large Language Models and Beyond](https://mlsanity.com/paper/2405.02213/) (2024)
- [Beyond the Comfort Zone: Emerging Solutions to Overcome Challenges in Integrating LLMs into Software Products](https://mlsanity.com/paper/2410.12071/) (2024)
- [Investigating the Role of Cultural Values in Adopting Large Language Models for Software Engineering](https://mlsanity.com/paper/2409.05055/) (2024)
- [Legal Aspects for Software Developers Interested in Generative AI Applications](https://mlsanity.com/paper/2404.16630/) (2024)

## Built on by (most cited first, 2 of 2)

- [Toward Expert Investment Teams:A Multi-Agent LLM System with Fine-Grained Trading Tasks](https://mlsanity.com/paper/2602.23330/) (2026)
- [AI Policies: Help or Hindrance? A Software Developer's Perspective](https://mlsanity.com/paper/2609.16496/) (2026)

## Abstract (arXiv)

The risks associated with adopting large language model (LLM) chatbots in software organizations highlight the need for clear policies. We examine how 11 companies create these policies and the factors that influence them, aiming to help managers safely integrate chatbots into development workflows.