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AI-Augmented Theory Building: From Theoretical Foundations to Practical Application

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  • Daniel Finkenstadt

    (Wolf Stake Consulting LLC)

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.

Suggested Citation

  • Daniel Finkenstadt, 2025. "AI-Augmented Theory Building: From Theoretical Foundations to Practical Application," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 12(1), pages 1-11, December.
    • Handle: RePEc:spr:custns:v:12:y:2025:i:1:d:10.1007_s40547-025-00155-8
    DOI: 10.1007/s40547-025-00155-8
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