From challenge to change: Design principles for AI transformations
Journal article, 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.

AI transformation

Organizational change

Behavioral Software Engineering

Artificial intelligence

Human-centered AI

Author

Theocharis Tavantzis

Aalborg University

Stefano Lambiase

Aalborg University

Daniel Russo

Aalborg University

Robert Feldt

Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)

University of Gothenburg

Journal of Systems and Software

0164-1212 (ISSN)

Vol. 243 113063

Subject Categories (SSIF 2025)

Information Systems, Social aspects

Software Engineering

Business Administration

DOI

10.1016/j.jss.2026.113063

More information

Latest update

8/28/2026