Redrawing the Lines: How AI Reshapes Labor Division in the Creative Advertising Industry

Artificial intelligence (AI) is reshaping the creative advertising industry, not just by automating discrete tasks, but by influencing how labor is divided, authority is distributed, and value is created and coordinated. Traditionally, advertising operated through a linear value chain, with clearly defined roles for clients, agencies, and media platforms. The emergence of AI tools introduces new possibilities and pressures, challenging institutional norms, reconfiguring workflows, and blurring boundaries between strategic, creative, and production functions. This thesis addresses a key gap: while technological and ethical dimensions of AI are explored, its institutional effects on labor division and inter-organizational dynamics in advertising remain underexplored. It is framed by the central research question: How is AI reshaping labor division between clients, agencies, and media platforms in the creative advertising industry? This study positions AI not only as a tool, but as a technological institution that may reshape how coordination, decision-making, and legitimacy are negotiated within the ecosystem. Drawing on Institutional Economics, particularly Transaction Cost Theory (TCT), path dependency, and power asymmetries, this thesis explores how roles and relationships evolve under technological change across five core advertising functions: strategy, creativity, production, distribution, and evaluation. The research follows a qualitative, exploratory approach based on nine semi-structured expert interviews with senior professionals from creative agencies operating in the Dutch market. Data were thematically coded in ATLAS.ti, combining inductive and interpretative strategies to identify institutional shifts in inter-organizational dynamics. The findings suggest that AI is not replacing human labor but redistributing and reframing it. Agencies are increasingly positioned as curators, advisors, and interpreters of AI-generated outputs, while clients internalize more production and planning tasks independently through accessible AI tools. Although media platforms were not a central focus of the interviews, they remain structurally influential through algorithmic governance and data-driven control over distribution and evaluation. Together, these dynamics signal an institutional transition from linear value chains to dynamic value networks, where collaboration becomes fluid, decentralized, and technologically mediated. By conceptualizing AI as an institutional force rather than just a tool, this thesis contributes to a deeper understanding of how automation and human agency interact to reshape norms, roles, and relationships that structure strategic and creative work in a rapidly evolving industry.