Becoming Certain About the Uncertain: How AI Changes Proof-of-Concept Activities in Manufacturing – Insights from a Global Automotive Leader

Abstract

In this paper, we examine Proof-of-Concept activities in the presence of Artificial Intelligence (AI).To this end, we conducted an exploratory, revelatory case study at a leading automotive OEM that constantly explores new technologies to improve its manufacturing processes. We highlight how AI properties affect specifics in project execution and how they are addressed within the focal company. We carved out four key areas affecting underlying activities, i.e., data assessment, process alignment, value orientation, and AI empowerment. With our findings, we provide practical insights into AI-related challenges and corresponding pathways for action. Drawn upon, we develop novel, timely, and actionable recommendations for AI project leaders planning to implement this novel technology in manufacturing. This shall provide empirically grounded and conceptually sound guidance for researchers and practitioners alike, and ultimately foster the success of AI in manufacturing.

Under Pressure: an Ethnographic Report from an Ambidextrous IPaaS Platform Entity

“…Many organizations appear to be at the stage where they are attempting to create a business case for AI. It is stated that many present-day AI initiatives and strategies fail, leading to a more pessimistic outlook (Alsheibani et al, 2019a;Sagodi et al, 2022). To combat this sentiment and help organizations further develop their initiatives, our research gives guidance on how to implement AI as an organization-wide change to help generate its proposed value and sustain AI efforts.…”

“…In this context, research on AI management and transformational change is scarce. The business-and strategy-oriented understanding of the management and long-term value-adding implementation of AI for enterprisewide change is still new to researchers and organizations even though it is a vital capability in the future (Fukas et al, 2021;Sagodi et al, 2022). Many organizations appear to be at the stage where they are attempting to create a business case for AI.…”

“…AI is a significantly disruptive technology for organizations (Benbya et al, 2020). At this point, 37% of global companies have incorporated AI into their businesses and products (Jovanovic, 2022), marking AI as a fast-growing technology and a fixed point on many more organizations' future agendas (Sagodi et al, 2022).…”

“…This is because AI comprises a complex bundle of technologies and applications, necessitating a new holistic understanding by managers of how to communicate, lead, coordinate, and control them (Berente et al, 2021). Additionally, it is also due to the different technological properties AI possess in comparison to conventional information systems (IS), such as, for example, being learning systems with black box characteristics and context-sensitivity (Sagodi et al, 2022). As a consequence of these challenges, organizations need to build capabilities for mastering new AI management activities, such as establishing data security and management, AI governance, AI strategic alignment, regulatory approvals for AI-based decisions, and ethical scrutiny of learning systems (Jöhnk et al, 2021;Kruse et al, 2019;Pumplun et al, 2019).…”