Library:
Madrid
London
Paris Champerret
Paris Montparnasse
Turin
Berlin
This master thesis investigates how artificial intelligence (AI) and collaborative tools influence
and enhance the design thinking methodology for driving corporate innovation. The study
identifies several important themes and insights through a qualitative analysis of in-depth
interviews with professionals from diverse corporate innovation teams and industries. By
analyzing the data from the interviews, the research identifies the practical implications,
benefits and challenges linked to incorporating AI and collaborative tools within the design
thinking methodology. The results show that artificial intelligence (AI) technologies can assist
and, enhance the different stages of the design thinking process,
including problem area identification, idea generation, fast prototyping, and user behaviour
analysis. However, the integration of AI tools must be moderated with human expertise, as an
over-reliance on AI runs the risk of reducing human creativity, which is essential to design
thinking. Throughout the design thinking process, collaborative tools like digital whiteboards
and prototyping platforms help enable teamwork, knowledge sharing, real-time collaboration,
and creating a common vision across remote and hybrid setups. However, challenges like
process integration and user adoption must be resolved. According to the research, some design
thinking stages—such research, ideation, and prototyping—benefit more from artificial
intelligence (AI) and collaborative technologies than others, like testing. It also
investigates how these technologies can enhance efficiency and support design thinking's
"failing fast" and rapid iteration principles. Overall, the study offers insightful advice on how
to strategically leverage AI and collaborative tools to support corporate innovation processes
while upholding the core human-centered approach of design thinking. Practical
recommendations and theoretical implications for corporations are discussed.
