AI Tool Use and Adoption in Software Development by Individuals and Organizations: A Grounded Theory Study

TL;DR

This study develops a grounded theory of AI tool adoption in software development, identifying motives, challenges, and relationships influencing individual and organizational use of AI tools like ChatGPT and Copilot.

Contribution

It provides a comprehensive theory of AI tool adoption, highlighting key motives, challenges, and interrelations based on empirical data from practitioners and surveys.

Findings

Identified motives such as sharing AI best practices.

Discovered challenges including organizational and individual barriers.

Revealed push-pull relationships affecting adoption decisions.

Abstract

AI assistance tools such as ChatGPT, Copilot, and Gemini have dramatically impacted the nature of software development in recent years. Numerous studies have studied the positive benefits that practitioners have achieved from using these tools in their work. While there is a growing body of knowledge regarding the usability aspects of leveraging AI tools, we still lack concrete details on the issues that organizations and practitioners need to consider should they want to explore increasing adoption or use of AI tools. In this study, we conducted a mixed methods study involving interviews with 26 industry practitioners and 395 survey respondents. We found that there are several motives and challenges that impact individuals and organizations and developed a theory of AI Tool Adoption. For example, we found creating a culture of sharing of AI best practices and tips as a key motive for practitioners' adopting and using AI tools. In total, we identified 2 individual motives, 4 individual challenges, 3 organizational motives, and 3 organizational challenges, and 3 interleaved relationships. The 3 interleaved relationships act in a push-pull manner where motives pull practitioners to increase the use of AI tools and challenges push practitioners away from using AI tools.