AI-Augmented Theory Building: From Theoretical Foundations to Practical Application
Daniel Finkenstadt ()
Additional contact information
Daniel Finkenstadt: Wolf Stake Consulting LLC
Customer Needs and Solutions, 2025, vol. 12, issue 1, No 6, 11 pages
Abstract:
Abstract This article explores how generative AI can augment, rather than replace, traditional theory-building processes in academic research. Drawing from foundational frameworks by Hunt (2010) [12] and Zeithaml et al. (J Mark 84(1):32–51, 2020), it presents a structured approach to integrating AI into theory development. The authors introduce Delegated Virtue Economics (DVE) as a case study that demonstrates AI’s role in accelerating ideation, identifying cross-disciplinary connections, and structuring conceptual models. They also highlight risks including source hallucination, over-reliance, and cognitive skill decay. The work outlines protocols for responsible human-AI collaboration and argues that the future of theory development lies in disciplined, symbiotic workflows that enhance both rigor and creativity.
Keywords: AI-augmented theory development; Delegated virtue economics; Human-AI collaboration; Scientific creativity barriers (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s40547-025-00155-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:custns:v:12:y:2025:i:1:d:10.1007_s40547-025-00155-8
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/40547
DOI: 10.1007/s40547-025-00155-8
Access Statistics for this article
Customer Needs and Solutions is currently edited by Min Ding
More articles in Customer Needs and Solutions from Springer, Institute for Sustainable Innovation and Growth (iSIG)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().