AI-Enhanced Design Thinking and Innovation Ma...

AI-Enhanced Design Thinking and Innovation Management: A Multifaceted Approach

Author Name : Audai Altaie

DOI: https://doi.org/10.56025/IJARESM.2024.2211241220

ABSTRACT

This study investigated the influence of AI on design thinking and innovation management of UK digital agency-based companies to enhance efficiency. However, this study employed a mixed-method study to understand the role of AI in design thinking processes and how it enhances innovation management. The quantitative study focused on exploring the influencing factors of innovation output (IO) in design thinking based on AI skillset and Expertise (ASE), level of AI integration (LAI), and implementation of AI technologies (IAI).

An online survey was conducted for participants (n=400) who are employees of UK-based digital agencies, such as CognitionX, Brainpool AI, Whoa, and The Data Lab. On the other hand, a semi-structured interview study was carried out for employees or managers (n=8) of companies.

The data findings from a quantitative study revealed that the level of AI integration has positively influenced the innovation output in the design thinking of companies. The qualitative study results depicted that these companies adopted AI tools successfully for training opportunities, design thinking, innovation management, and identification of trends and insights owing to the intuitive visualization and user-friendly features. Moreover, we identified challenges related to integration of AI, scalability, compatibility, and data privacy and security. These challenges could be alleviated by providing organizational support in terms of regular training, technical resources, cross-departmental collaboration, and personalized training about integrating AI into existing systems of design thinking procedures. Therefore, this study proved that AI tools enhance creativity and efficiency in design thinking and foster innovation in organizations. 

Keywords: Artificial Intelligence, Design Thinking, Innovation Management, Mixed-method Study, Efficiency.