Helpful but Fallible: Developer Experiences of AI Tools Under a Coordinated Industrial Roll-out

2026-09-17

AI Summary

研究通过半结构化访谈和TAM2模型分析了AI开发工具在一家瑞典电信公司的推广情况，探讨了开发者体验及对未来职业变化的看法。

Abstract

AI-enabled software development tools (AI-devtools) are being industrially adopted under strong expectations of productivity gains, yet developers' experiences of such roll-outs are underexplored. Organizations commit budgets, evaluate staff, and revise practice on a partial picture, since the evidence base is mainly tool evaluations, productivity metrics, and surveys, with few qualitative in-situ accounts of ongoing, coordinated roll-outs. We report a case study of a coordinated roll-out of AI-devtools at a large Swedish telecommunications company, investigating how developers experience the roll-out and how they anticipate their profession will change. We conducted semi-structured interviews with 12 software professionals across three sites, analyzed with process coding and thematic analysis, and interpreted through the extended Technology Acceptance Model (TAM2) as a post-hoc analytical lens. Our findings on use cases, productivity, frustrations, and tool limitations corroborate prior survey work. Beyond corroboration, the interviews surface a management-developer expectation gap that maps onto the TAM2 constructs of subjective norm and voluntariness, and show that participants weigh perceived risk heavily, a factor that TAM2 and similar acceptance models do not represent. AI-devtools emerge as helpful but fallible assistants whose value is shaped by organizational expectations, system scale, and developers' skills.

Problem

• AI-devtools
• developer experiences
• industrial roll-out
• productivity gains
• qualitative in-situ accounts

Innovation

• AI-devtools
• qualitative in-situ accounts
• Technology Acceptance Model (TAM2)
• management-developer expectation gap
• perceived risk