A New Team Structure for AI-Human Collaboration in Digital Product Development

Adoption of artificial intelligence in organizations is growing so fast. This highlighted a quick need for new team structures that blend human and AI members. This dissertation investigates AI’s integration as an active team member in cross-functional, digital product development teams. This research presents a new team structure to improve AI-human collaborations in these teams.

Implementing an interpretivist, inductive methodology, this research work involved professionals from product management, engineering, and marketing in semi-structured interviews. These interviews explore current team challenges and people’s perceptions about AI’s role.

After thematic analysis of the qualitative data, four common pain points in these teams were revealed. These teams include misaligned goals, conflicting KPIs, communication gaps, and cultural clashes. These conflicts often reduce performance and collaborative work in teams. Participants in this study perceived AI as a beneficial partner to help them resolve these issues. After synthesizing insights from data and existing literature, the thesis offers a conceptual model for AI integration. In this model, the AI agent is an analyst who has complementary roles. This model illustrates how AI’s data-driven capabilities directly address human collaboration challenges.

Finally, this thesis work offers practical suggestions for organizations to implement the suggested model effectively. It emphasizes considering role clarity, trust building, ethical governance and data oversight, and continuous learning. This research extends team dynamics frameworks to contribute to management theory. It includes non-human members and provides organizations with a timely framework for improving their teams’ performance through the AI-human synergy effect.
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EditionNo. 29AuthorMahnaz JaldiYear2025Download PDFcreativeindustries.berlin