AI in the Creative Industries: A Comprehensive Study of AI's Influence on Graphic Design, its Effects on the Creative Production Process, Collaborative Dynamics, and Market Trends

Abstract

In a world where technology and creativity collide, the ever-evolving landscape of generative AI has emerged as a dynamic force, reshaping the field of the creative industries. Since the end of 2022, generative AI has created a big discussion about the value of designers and artists. Yet, given the short timeframe, research in computational creativity shows big gaps in the changes creative professionals must deal with. Previous literature anticipated heightened productivity and efficiency through human-AI collaboration, shedding light on profound market changes in job roles and skills within the creative industries. The goal of this master's thesis is to investigate alterations in productivity and efficiency in the creative process for graphic designers due to AI. It explores modifications in the creative production process, collaboration with generative AI, and business implications like job displacement, new roles, and skill development. The study collects data using an inductive, qualitative approach based on n=15 semi-structured interviews. The findings reveal that effective collaboration with AI enhances designers' efficiency in the production process, but since resources are directed towards more high-value tasks, the overall productivity of the process remains unchanged. The design market notes a decline in basic design jobs, signalling an evolution in designers' roles, particularly in Art and Creative Direction. New technical roles like operational engineers and creative quality assurance directors are emerging, emphasizing proficiency in navigating and curating AI tools. Designers must acquire management, communication, and technology skills while maintaining mental and creative flexibility to adapt to evolving ideas. This research adds to existing literature by exploring AI's practical impact on graphic designers, emphasizing the enduring human role, opportunities, and limits of AI-related tasks, and suggests new directions for further exploration in academia.