From challenge to change: Design principles for AI transformations

Artikel i vetenskaplig tidskrift, 2027

The rapid rise of Artificial Intelligence (AI) technologies is reshaping Software Engineering (SE) practice, unlocking new opportunities while introducing human-centered challenges. Although prior research acknowledges behavioral and other non-technical factors affecting AI integration, most studies still emphasize technical concerns and offer limited insight into how teams adapt to and trust AI systems. This work proposes a Behavioral Software Engineering (BSE)-informed, human-centric framework to support SE organizations during early AI adoption. We employed a mixed-methods methodology to construct and refine the framework. A literature review of organizational change models established its theoretical foundation, and thematic analysis of interview data produced concrete, actionable steps. The resulting 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 actionable steps. To collect preliminary practitioner feedback, we conducted a survey (N=105) and two expert workshops (N=4). Survey responses show that Up-skilling (15.2 %) and AI Strategy Design (15.1 %) received the highest $100-method allocations, highlighting their perceived centrality in early AI initiatives. Findings suggest that organizations currently prioritize procedural aspects such as strategy design, while human-centered guardrails remain comparatively underdeveloped. Early feasibility checks of the workshops reinforced these patterns and highlighted the importance of grounding the framework in real-world practice. By identifying critical behavioral dimensions and offering actionable guidance, this contribution provides practitioners with a pragmatic roadmap for navigating the socio-technical complexity of early AI adoption and outlines future research directions for human-centric AI in SE.