The rapid evolution and inherent complexity of modern software requirements demand highly flexible and responsive development methodologies. While Agile frameworks have become the industry standard for prioritizing iteration, collaboration, and adaptability, software development teams continue to face persistent challenges in managing constantly evolving requirements and maintaining product quality under tight deadlines. This article explores the intersection of Artificial Intelligence (AI) and Software Engineering (SE), to analyze how AI serves as a powerful catalyst for enhancing agility and fostering innovation. The research combines a comprehensive review of existing literature with an empirical study, utilizing a survey directed at Software Engineering professionals to assess the perception, adoption, and impact of AI-driven tools. Key findings reveal that the integration of AI (specifically through Machine Learning (ML) and Natural Language Processing (NLP) )facilitates the automation of tedious tasks, from requirement management to code generation and testing . This paper demonstrates that AI not only optimizes current Agile practices but also introduces new capabilities essential for sustaining quality, speed, and innovation in the future landscape of software development.

翻译：现代软件需求的快速演进与固有复杂性要求高度灵活且响应迅速的开发方法。尽管敏捷框架已成为业界优先迭代、协作与适应性的标准，软件开发团队在管理不断变化的需求及紧迫时限下维持产品质量方面仍面临持续挑战。本文探讨人工智能与软件工程的交叉领域，以分析AI如何作为增强敏捷性与促进创新的强大催化剂。本研究结合现有文献综述与实证研究，通过对软件工程专业人员开展问卷调查，评估AI驱动工具的认知度、采纳度与影响。关键发现表明，人工智能的集成（特别是通过机器学习与自然语言处理技术）促进了从需求管理到代码生成与测试等繁琐任务的自动化。本文论证了AI不仅能够优化现有敏捷实践，更能引入对维持未来软件开发领域质量、速度与创新至关重要的新型能力。