STRATEGIC ALIGNMENT IN GENERATIVE AI ENGINEERING TEAMS: A qualitative investigation of alignment factors in an AI engineering team

Sammanfattning

The rapid advancement of generative AI has given rise to AI engineering as a new discipline, where teams face challenges that differ from those of traditional software engineering. One such challenge is aligning strategic intent with delivery outcomes as rapidly evolving technology, emerging roles, and shifting work practices compli-cate the translation of strategy into execution. While prior research has examined strategic alignment in software engineering and organizational challenges in AI and ML development, limited research has specifically addressed how these dynamics unfold in generative AI engineering teams. This study aims to identify and analyze the factors that affect alignment between strategic intent and delivery outcomes in such teams. The study is guided by the research question: What factors affect align-ment between strategic intent and delivery outcomes in generative AI engineering teams? A qualitative approach was applied, based on semi-structured interviews with six members of an AI engineering team at a large global organization. The empirical material was analyzed through thematic analysis and interpreted using Leavitt's Di-amond as a theoretical lens, examining the dimensions of task, people, technology, and structure. The study identifies twelve factors distributed across the four dimen-sions and demonstrates how they interact to shape alignment. The findings suggest that alignment in generative AI engineering teams does not happen automatically, but emerges continuously through the interplay of technological change, evolving work practices, team adaptability, and structural coordination between engineers, management, and stakeholders.