LLM Company Policies and Policy Implications in Software Organizations

2025-10-08

AI Summary

This study addresses the absence of organizational policies for securely integrating large language model (LLM)-based chatbots into software development workflows. Through a qualitative multi-case study involving 11 enterprises—including in-depth interviews, internal policy document mining, and textual analysis—it provides the first systematic examination of how enterprise-level LLM policies emerge and the key drivers shaping them. The research identifies a recurring trade-off among security, regulatory compliance, and development efficiency, and distills four core policy dimensions: risk identification, access control, data governance, and auditability. Based on these findings, the study proposes a scalable, enterprise-grade LLM governance framework. Designed for practical deployment, the framework offers managers an adaptable, actionable guide for integrating AI tools into existing software engineering practices while mitigating associated risks.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Natural Language Processing: Safety and Robustness
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness

Application Category

• User Modeling, Personalization and Recommendation: Large Language Models (LLM) for user modeling and recommendation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems

Abstract

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.

Problem

• Examining company policies for LLM chatbot adoption risks
• Analyzing factors influencing policy creation in software organizations
• Helping managers safely integrate chatbots into development workflows

Innovation

• Examining company policies for LLM chatbots
• Analyzing factors influencing policy creation
• Helping managers integrate chatbots safely