Design Thinking for Artificial Intelligence: How Design Thinking Can Help Organizations to Address Common AI Project Challenges

Staub, Laura; van Giffen, Benjamin; Hehn, Jennifer; Sturm, Simon (28 July 2023). Design Thinking for Artificial Intelligence: How Design Thinking Can Help Organizations to Address Common AI Project Challenges In: Degen, H.; Ntoa, S.; Moallem, A. (eds.) HCI International 2023: Late Breaking Papers. Lecture Notes in Computer Science: Vol. 14059 (pp. 251-267). Cham: Springer 10.1007/978-3-031-48057-7_16

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The last decade indicates a drastic upswing in the adoption of organizational artificial intelligence (AI). Companies increasingly seize the transformative potential AI entails to enhance the effectiveness and efficiency of various business functions. However, studies show that over 85% of all AI projects in organizations fail to be implemented. Therefore, this study investigates the most common AI project management challenges that prevent organizations from successfully deploying AI initiatives. It further explores how the human-centered innovation method design thinking (DT) can address these challenges. To do so, a multiple-case study with a single-unit of analysis was conducted, whereby twenty representatives from ten companies and startups were interviewed. Findings show that in practice, the six most frequently occurring AI project management challenges are: the lack of education around the topic and the resulting distrust in such technology; the missing user-centricity that leads to the development of undesired solutions; the fact that pre-defined solutions hinder project teams from adequately analyzing the business problem first; the insufficient cross-department collaboration and communication; and the absence of high-quality data. Moreover, it was found, that the four overarching DT elements which help organizations tackle these problems are the Needfinding phase, where relevant stakeholders are interviewed and questioned about their pain-points, wishes, and needs at the beginning of the process; the early Prototype Testing where end users can experience the prototypes themselves; the DT Mindset, which entails human-centered thinking, collaboration, integrity, diversity, and empathy, amongst others; and DT as a Process Structure along which AI-driven projects can be developed. Based on insights from this empirical research, suggestions are made which organizations can follow to directly address AI project management challenges and, thereby, increase their rate of successfully deployed AI projects.

Item Type:	Conference or Workshop Item (Paper)
Division/Institute:	Business School > Institute for Digital Technology Management Business School
Name:	Staub, Laura; van Giffen, Benjamin; Hehn, Jennifer0000-0002-3961-6377; Sturm, Simon; Degen, H.; Ntoa, S. and Moallem, A.
ISBN:	978-3-031-48056-0
Series:	Lecture Notes in Computer Science
Publisher:	Springer
Language:	English
Submitter:	Jennifer Hehn
Date Deposited:	08 Dec 2023 09:59
Last Modified:	12 Dec 2023 14:31
Publisher DOI:	10.1007/978-3-031-48057-7_16
Related URLs:	Organisation
URI:	https://arbor.bfh.ch/id/eprint/20570