Leadership cognition and AI-enabled market intelligence: Building adaptive personalization in competitive service markets
Purpose of the research This study examines how top management team (TMT) cognition shapes the development of adaptive personalization in emerging-market service firms. Drawing on upper echelons theory, this study tests a model in which TMT risk appetite and strategic vision drive adaptive personalization through AI-enabled market intelligence (AIMI), with competitive rivalry acting as a boundary condition. Major findings Multi-source, time-lagged data collected from TMT members, managers, and repeat customers are aggregated for 139 firms in the Pakistani tourism and hospitality sector. The results show that competitive rivalry amplifies the influence of TMT cognition on AIMI adoption, reflecting the heightened strategic pressures characteristic of emerging markets. This study contributes to the literature by (1) advancing a psychological micro-foundations perspective of upper echelons theory, (2) introducing adaptive personalization as a cognition-driven dynamic capability, and (3) integrating managerial cognition with AI-enabled strategic processes. Conclusions This study advances upper echelons theory by explaining adaptive personalization as a leadership-driven capability shaped by TMT risk appetite and strategic vision rather than as a purely technology-led outcome. The study offers a novel account of how executive cognition supports AI-enabled transformation in emerging-market service firms.
Authors
- Mohit Kukreti (ORCID: https://orcid.org/0000-0003-0067-0103)
- Sami Ullah (ORCID: https://orcid.org/0000-0002-1898-8374)
- Aarti Dangwal (ORCID: https://orcid.org/0000-0002-1411-3650)
- Abdul Sami (ORCID: https://orcid.org/0000-0001-7343-3526)
- Yuhao Su (ORCID: https://orcid.org/0009-0008-5687-941X)
Institutions
- Henan University (CN)
- University of Central Punjab (PK)
- University of Technology and Applied Sciences — Ibri (OM)
- Chitkara University (IN)
Publication Details
- Journal
- Human Systems Management
- Published
- 2026-09-28
- DOI
- https://doi.org/10.1177/01672533261492901
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00