As AI increasingly performs tasks once requiring deep technical expertise, software engineering faces a paradox. Programmers are simultaneously at risk of deskilling while being pushed to acquire new forms of knowledge and responsibility. However, AI can shift core competencies, reshape workflows, and redistribute responsibilities, offering a framework for organizations and developers to adapt strategically. Professional software engineers may use intelligent tools for improved upskilling and reskilling, identifying new skills required to remain competitive and effective. Further exploration may provide clarity for decision-makers navigating emerging debates around automation, workforce displacement, AI reliability, and ethical development practices. AI Impacts on Deskilling and Reskilling Software Engineers explores how generative AI tools reshape the foundations, workflows, and professional identities of software engineers. It examines how automation changes what developers do and think, addressing the shifting skill demands in software engineering, from traditional coding proficiency to AI oversight, prompt design, architecture-level reasoning, collaboration, and ethical decision-making. This book covers topics such as skill development, IT management, and system design, and is a useful resource for engineers, business owners, academicians, researchers, and scientists.
