Strategic Leadership in AI-Enhanced Aviation: Balancing Financial and Environmental Goals Through Differentiated Search

SeyyedAbdolHojjat  MoghadasNian,Parvin  Karimi

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Эта статья является препринтом и не была отрецензирована.
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Strategic Leadership in AI-Enhanced Aviation: Balancing Financial and Environmental Goals Through Differentiated Search

S. MoghadasNian,

P. Karimi

2026-01-18

https://doi.org/10.24108/preprints-3114300

This study examines how strategic leadership styles shape the integration of artificial intelligence (AI) in airline operations, highlighting both financial performance and sustainability outcomes. A mixed-method design was employed, combining semi-structured interviews, archival operational reports, and document analyses of AI initiatives. Central to this research are multi-objective optimization algorithms including evolutionary computing and reinforcement learning that simultaneously improve cost-effectiveness and reduce environmental impacts. The findings show that transformational leadership fosters broad AI adoption, notably in areas like predictive maintenance and emission reduction, whereas transactional leadership tends to emphasize short-term efficiency gains. Quantitatively, evolutionary algorithms and reinforcement learning consistently produce cost reductions of 7–12% while yielding fuel savings of 6–10%, underscoring their potential to balance profitability with ecological responsibility. From a theoretical standpoint, these insights enrich leadership and digital transformation frameworks by illustrating how executive behaviors and complex AI technologies interact to achieve dual financial and environmental benefits. In practical terms, the study recommends forming cross-functional governance committees, enhancing leadership training to encourage visionary communication, and adopting phased AI deployments to manage elevated risk tolerance. To operationalize these findings, Appendix A provides a set of role-based Key Performance Indicators (KPIs) for financial performance and sustainability, offering practitioners a clear metric framework for measuring progress. Overall, this research underscores the need to align AI-driven analytics with strategic leadership competencies and robust oversight mechanisms, presenting a roadmap to optimize costs, meet sustainability targets, and ensure resilient decision-making in the ever-evolving aviation sector.

Ссылка для цитирования:

MoghadasNian S., Karimi P. 2026. Strategic Leadership in AI-Enhanced Aviation: Balancing Financial and Environmental Goals Through Differentiated Search. PREPRINTS.RU. https://doi.org/10.24108/preprints-3114300

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