Developing a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development
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Abstract (arXiv)
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.
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References · 12
- 2017Attention Is All You Needcited by 60,361
- 2024Using AI-Based Coding Assistants in Practice: State of Affairs, Perceptions, and Ways Forwardcited by 45
- 2024Human-In-the-Loop Software Development Agentscited by 42
- 2023Navigating the Complexity of Generative AI Adoption in Software Engineeringcited by 32
- 2023Exploring and Characterizing Large Language Models For Embedded System Development and Debuggingcited by 20
- 2023Building Your Own Product Copilot: Challenges, Opportunities, and Needscited by 17
- 2026How Well Does Agent Development Reflect Real-World Work?cited by 10
- 2025Agent for User: Testing Multi-User Interactive Features in TikTokcited by 5
- 2026Agentic AI in Industry: Adoption Level and Deployment Barrierscited by 4
- 2025Securing LLM-Generated Embedded Firmware through AI Agent-Driven Validation and Patchingcited by 3
- 2025Walking the Tightrope of LLMs for Software Development: A Practitioners' Perspectivecited by 2
- 2026Agentic Pipelines in Embedded Software Engineering: Emerging Practices and Challengescited by 2
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- 2025The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering
- 2025From Challenge to Change: Design Principles for AI Transformations ↗
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