Generative AI (GenAI) is reshaping enterprise architecture work in agile software organizations, yet evidence on its effects remains scattered. We report a systematic literature review (SLR), following established SLR protocols of Kitchenham and PRISMA, of 1,697 records, yielding 33 studies across enterprise, solution, domain, business, and IT architect roles. GenAI most consistently supports (i) design ideation and trade-off exploration; (ii) rapid creation and refinement of artifacts (e.g., code, models, documentation); and (iii) architectural decision support and knowledge retrieval. Reported risks include opacity and bias, contextually incorrect outputs leading to rework, privacy and compliance concerns, and social loafing. We also identify emerging skills and competencies, including prompt engineering, model evaluation, and professional oversight, and organizational enablers around readiness and adaptive governance. The review contributes with (1) a mapping of GenAI use cases and risks in agile architecting, (2) implications for capability building and governance, and (3) an initial research agenda on human-AI collaboration in architecture. Overall, the findings inform responsible adoption of GenAI that accelerates digital transformation while safeguarding architectural integrity.

翻译：生成式人工智能（GenAI）正在重塑敏捷软件组织中的企业架构工作，然而其影响的证据仍较为零散。我们遵循Kitchenham和PRISMA确立的系统性文献综述（SLR）规范，对1,697条记录进行了系统性文献综述，最终纳入了涵盖企业、解决方案、领域、业务和IT架构师角色的33项研究。GenAI最一致地支持（i）设计构思与权衡探索；（ii）工件的快速创建与精炼（例如代码、模型、文档）；（iii）架构决策支持与知识检索。报告的风险包括不透明性与偏见、情境错误输出导致返工、隐私与合规性问题，以及社会惰化现象。我们还识别了新兴的技能与能力，包括提示工程、模型评估和专业监督，以及围绕准备度和适应性治理的组织赋能因素。本综述的贡献在于：（1）绘制了敏捷架构中GenAI的用例与风险图谱；（2）提出了能力建设与治理的启示；（3）初步构建了架构领域人机协作的研究议程。总体而言，研究结果为负责任地采用GenAI提供了参考，旨在加速数字化转型的同时保障架构完整性。