The impact of applying generative AI tools to requirements engineering (RE) in industrial practice remains poorly understood. This paper examines how AI-assisted RE tools are used in industrial practice at XITASO, a medium-sized enterprise for high-tech software engineering, and how they reshape workflows, tool integration, and PO--developer relationships. We combine a 2024 company-wide use-case survey with two rounds of semi-structured interviews with eight product owners (POs) in late 2025 and spring 2026, covering an in-house chatbot and seven commercial AI tools. We identify 15 distinct use cases across four categories: product backlog management, tender management, requirements and domain understanding, and document and artifact creation. Three findings emerge. First, the effect of AI on PO--developer interaction is mixed: the prevailing single-user interaction model can substitute for collaborative dialogue, and developers do not always welcome AI-generated artefacts. Second, tool integration -- not tool capability -- is the binding constraint: where integration is in place, time savings are dramatic; where it is missing, POs fall back on manual workarounds. Third, AI advances faster than the surrounding organisational systems, so its benefits accrue to individual POs while team processes and customer readiness remain the limiting factors. AI-assisted RE in practice is more advanced than the GenAI-RE literature reflects: practitioners are already assembling cross-tool integrations, navigating customer governance, and renegotiating role boundaries in ways that evaluations focused on isolated tasks and single-engineer scenarios do not capture. From these patterns we derive a set of questions practitioners considering AI-assisted RE may ask of their own situation.

翻译：将生成式AI工具应用于工业实践中的需求工程（RE）所产生的影响仍未被充分理解。本文以中型高科技软件工程企业XITASO为研究对象，探讨AI辅助需求工程工具在工业实践中的实际应用，以及这些工具如何重塑工作流程、工具集成与产品负责人（PO）-开发者关系。我们结合一项2024年全公司的用例调查，于2025年末和2026年春对八位产品负责人进行了两轮半结构化访谈，涵盖了一款内部聊天机器人和七款商业AI工具。我们识别了四大类共15个不同用例：产品待办事项管理、招标管理、需求与领域理解，以及文档与工件生成。研究得出三项发现：第一，AI对PO-开发者交互的影响具有双重性——当前主流的单用户交互模式可能替代协作对话，且开发者并非总是欢迎AI生成的工件；第二，工具集成（而非工具能力）是制约性瓶颈——当集成到位时，时间节省效果显著，反之PO则需依赖人工变通方案；第三，AI的发展速度超过其周围的组织系统，因此其收益主要惠及个体PO，而团队流程和客户准备度仍是限制因素。实践中的AI辅助RE比GenAI-RE文献所反映的更为先进：从业者已开始构建跨工具集成、应对客户治理问题、并重新协商角色边界，而现有以孤立任务和单工程师场景为焦点的评估方法无法捕捉这些实践。基于这些模式，我们提炼出一系列供考虑采用AI辅助RE的从业者结合自身情境进行反思的问题。