๐ค AI Summary
This study addresses the transformative challenges that increasing AI agent autonomy poses to team structures, competencies, and strategies within embedded software organizations. Drawing on a case study of a large-scale embedded systems enterprise, the research employs semi-structured workshops and a mixed-methods approach to conduct an empirical analysis. The work proposes a federated AI team-building model alongside a humanโmachine collaboration practice framework. Furthermore, it elucidates the profound impact of AI integration on organizational roles and capabilities, ultimately delivering a sustainable transformation roadmap for organizations transitioning toward an AI-first paradigm.
๐ Abstract
The emergence of AI agents is expected to reshape software engineering by moving beyond AI as assistants towards systems capable of planning, executing, and evaluating development tasks with increasing autonomy. This transition is particularly significant for embedded software organizations, where strict requirements for quality, traceability, verification, and long-term maintainability often apply. This paper presents a case study of a large embedded systems company and its transition toward becoming an AI-first organization. Through a mixed method, we analyzed data collected from a semi-structured workshop with 40 participants, including scrum masters, architects, management, and product owners. The findings show that the participants expect agentic AI to affect team structure, required competencies, organizational strategies, and developers' roles within the organization. Based on these findings, the paper discusses implications for federated AI team formation, human-in-the-loop practices in such an organization, and the sustainable adoption of AI agents in embedded software engineering. We also present a concrete roadmap for the organization towards becoming an AI-first organization.