Dissertation
Artificial intelligence hiring as strategic capability building: an empirical analysis of firm-level determinants in the consumer packaged goods industry
Doctor of Business Administration (D.B.A.), Drexel University
May 2026
DOI:
https://doi.org/10.17918/00011408
Abstract
Artificial intelligence (AI) has emerged as a strategic priority for firms seeking to improve innovation, efficiency, and competitiveness. Despite its potential, adoption within the consumer packaged goods (CPG) industry remains uneven, and little is known about how firms build AI-related capabilities during the early stages of digital transformation. This study examines AI hiring intensity as a forward-looking indicator of organizational capability development within a mature industry characterized by legacy systems, fragmented data environments, and organizational complexity. Drawing on the Resource-Based View, Dynamic Capabilities Theory, Strategic Human Capital Theory, and Complementarity Theory, this study investigates the firm-level determinants of AI hiring intensity and its relationship with short-term organizational performance. Using a cross-sectional sample of 43 publicly traded U.S. CPG firms, AI hiring intensity was measured as the proportion of AI-related job postings relative to total job postings observed between April and October 2025. Firm-level financial and organizational data were obtained from Compustat and company filings. Ordinary least squares regression models with robust standard errors were used to evaluate the proposed relationships. Results indicate that organizational scale, particularly employee count, is the strongest and most consistent predictor of AI hiring intensity. In contrast, sales growth, Tobin's Q, R&D intensity, and industry classification were not significant predictors in the primary models. AI hiring intensity also demonstrated weak and inconsistent relationships with short-term performance measures, including return on assets, sales growth, and stock price performance. The findings suggest that AI-related hiring reflects an early-stage capability-building process rather than an immediate driver of financial performance. By introducing AI hiring intensity as a measure of emerging technological capability, this study contributes to research on digital transformation and provides insight into how firms in mature industries invest in AI-related capabilities prior to realizing measurable performance outcomes.
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Details
- Title
- Artificial intelligence hiring as strategic capability building
- Creators
- Alexandra May Derevianko
- Contributors
- Gregory Nini (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Business Administration (D.B.A.)
- Publisher
- Drexel University
- Number of pages
- 108 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Bennett S. LeBow College of Business; Drexel University
- Other Identifier
- 991022189371804721