A1 Journal article (refereed)
How could Generative AI support and add value to non-technology companies : A qualitative study (2025)

Modgil, S., Gupta, S., Kar, A. K., & Tuunanen, T. (2025). How could Generative AI support and add value to non-technology companies : A qualitative study. Technovation, 139, Article 103124. https://doi.org/10.1016/j.technovation.2024.103124

JYU authors or editors

Publication details

All authors or editors: Modgil, Sachin; Gupta, Shivam; Kar, Arpan Kumar; Tuunanen, Tuure

Journal or series: Technovation

ISSN: 0166-4972

eISSN: 1879-2383

Publication year: 2025

Publication date: 19/10/2024

Volume: 139

Article number: 103124

Publisher: Elsevier

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1016/j.technovation.2024.103124

Publication open access: Not open

Publication channel open access: 

Abstract

With the spread of generative AI, non-technology companies are also adopting it at a faster rate. Therefore, this study aims to study the appropriation of Generative AI to create value to non-technology businesses through a knowledge based view of the firm. To achieve this objective, we followed a semi-structured interview schedule, where 98 qualitative data points were collected and analysed. We follow open, axial and selective coding along with Gioia methodology for analysis. Findings indicate that companies employ Generative AI for risk management, where potential threats, impact of possible hazards and degree of uncertainty in the business environment are considered in decision-making. Generative AI also helps in knowledge integration, where assimilation, adaptation, application and implementation are achieved. Findings also suggest that an improved business outlook can be achieved regarding accurate demand forecasting, real-time insights, contextual understanding and alignment to the vision through Generative AI. It is also observed that companies are investing in Generative AI to achieve competitive advantage and greater significance. The contribution of this study lies in the development of four propositions and a framework for generative AI-driven value for non-technology companies. The framework also uncovers the internal flow among key elements from risk identification to integration to developing the outlook and driving utility.

Keywords: business models; artificial intelligence; surplus value; business value; technological development; qualitative analysis (chemical analysis)

Free keywords: qualitative study; generative artificial intelligence; business value; business model; technology appropriation

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