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Abstract: The rapid proliferation of artificial intelligence (AI) technologies has created a significant demand for skilled professionals, particularly in AI software engineering. This article presents a comprehensive framework for facilitating the career transition of software engineers into the AI domain. Through a mixed-methods approach, incorporating both qualitative interviews with industry experts and a quantitative survey of professionals who have successfully transitioned to AI roles, we identify key components of an effective transition strategy. Our findings reveal a multi-faceted process encompassing skill assessment, targeted learning pathways, practical experience acquisition, and strategic networking. The proposed framework addresses common obstacles in the transition process and provides evidence-based strategies for overcoming them. Additionally, we explore the critical role of continuous learning in maintaining relevance in the rapidly evolving AI field. This article contributes to the growing body of literature on career adaptation in the face of technological change and offers practical implications for individuals, employers, and educational institutions navigating the AI talent landscape. Our findings suggest that with a structured approach and commitment to ongoing development, software engineers can successfully pivot their careers to meet the growing demand for AI expertise
Subash Patel (Fri,) studied this question.