The rapid rise of Artificial Intelligence (AI) is reshaping Software Engineering (SE), creating new opportunities while introducing human-centered challenges. Although prior work notes behavioral and other non-technical factors in AI integration, most studies still emphasize technical concerns and offer limited insight into how teams adapt to and trust AI. This paper proposes a Behavioral Software Engineering (BSE)-informed, human-centric framework to support SE organizations during early AI adoption. Using a mixed-methods approach, we built and refined the framework through a literature review of organizational change models and thematic analysis of interview data, producing concrete, actionable steps. The framework comprises nine dimensions: AI Strategy Design, AI Strategy Evaluation, Collaboration, Communication, Governance and Ethics, Leadership, Organizational Culture, Organizational Dynamics, and Up-skilling, each supported by design principles and actions. To gather preliminary practitioner input, we conducted a survey (N=105) and two expert workshops (N=4). Survey results show that Up-skilling (15.2%) and AI Strategy Design (15.1%) received the highest $100-method allocations, underscoring their perceived importance in early AI initiatives. Findings indicate that organizations currently prioritize procedural elements such as strategy design, while human-centered guardrails remain less developed. Workshop feedback reinforced these patterns and emphasized the need to ground the framework in real-world practice. By identifying key behavioral dimensions and offering actionable guidance, this work provides a pragmatic roadmap for navigating the socio-technical complexity of early AI adoption and highlights future research directions for human-centric AI in SE.

翻译：人工智能的迅速崛起正在重塑软件工程领域，在创造新机遇的同时也带来了以人为中心的挑战。尽管先前的研究指出了人工智能整合中的行为因素及其他非技术性因素，但大多数研究仍侧重于技术问题，对团队如何适应并信任人工智能的洞察有限。本文提出一个基于行为软件工程、以人为中心的框架，以支持软件工程组织在早期人工智能采用阶段的发展。通过混合研究方法，我们结合组织变革模型的文献综述与访谈数据的主题分析，构建并完善了该框架，提出了具体且可操作的步骤。该框架涵盖九个维度：人工智能战略设计、人工智能战略评估、协作、沟通、治理与伦理、领导力、组织文化、组织动态以及技能提升，每个维度均辅以设计原则和行动建议。为收集初步的从业者意见，我们开展了一项调查（N=105）和两场专家研讨会（N=4）。调查结果显示，技能提升（15.2%）和人工智能战略设计（15.1%）在100美元分配法中获得了最高比例，突显了它们在早期人工智能项目中的重要性。研究发现表明，组织当前优先关注战略设计等程序性要素，而以人为中心的保障机制仍较不完善。研讨会反馈进一步印证了这些模式，并强调需将框架根植于实际实践。通过识别关键行为维度并提供可操作的指导，本研究为应对早期人工智能采用中的社会技术复杂性提供了实用路线图，并指明了软件工程中以人为中心人工智能的未来研究方向。