Version 1
: Received: 22 September 2024 / Approved: 23 September 2024 / Online: 23 September 2024 (16:47:24 CEST)
How to cite:
Frimpong, V. Artificial Intelligence in Business History Analysis: Implications for Contemporary Management and Ethical Leadership. Preprints2024, 2024091817. https://doi.org/10.20944/preprints202409.1817.v1
Frimpong, V. Artificial Intelligence in Business History Analysis: Implications for Contemporary Management and Ethical Leadership. Preprints 2024, 2024091817. https://doi.org/10.20944/preprints202409.1817.v1
Frimpong, V. Artificial Intelligence in Business History Analysis: Implications for Contemporary Management and Ethical Leadership. Preprints2024, 2024091817. https://doi.org/10.20944/preprints202409.1817.v1
APA Style
Frimpong, V. (2024). Artificial Intelligence in Business History Analysis: Implications for Contemporary Management and Ethical Leadership. Preprints. https://doi.org/10.20944/preprints202409.1817.v1
Chicago/Turabian Style
Frimpong, V. 2024 "Artificial Intelligence in Business History Analysis: Implications for Contemporary Management and Ethical Leadership" Preprints. https://doi.org/10.20944/preprints202409.1817.v1
Abstract
The emergence of Artificial Intelligence (AI) has transformed the way historical data is interpreted, uncovering previously unseen trends and fundamentally altering modern management practices. This shift has significantly impacted the analysis of business history and leadership studies. However, there is still a notable gap in research regarding the effects of AI-driven reinterpretations of historical events on contemporary business strategies, leadership frameworks, and ethical considerations. This study aims to address this gap by exploring the methodologies and implications of AI in business history analysis, focusing on case studies of Walmart and JPMorgan Chase. Integrating foundational theories such as evolutionary theory, path dependency, transformational, and authentic leadership reveals how AI-driven insights can refine strategic planning, advance leadership development, and promote equitable management practices. It also highlights the ethical challenges in using AI for historical analysis, particularly the risks of perpetuating existing biases. Findings indicate that AI's capacity to analyze large volumes of historical data significantly reshapes our understanding of business evolution and leadership effectiveness. The study concludes with actionable recommendations for adopting ethical AI practices, outlining future research directions, including developing AI models for contextual analysis and exploring AI’s role in promoting diverse leadership models. This research advances academic discourse by providing a theory-driven framework for leveraging AI in business history and leadership studies. It underscores AI's transformative potential and complex implications for future business practices.
Keywords
Artificial Intelligence (AI), Business History Analysis, Leadership Models, Ethical AI, Strategic Management. Historical Reinterpretation, AI-Driven Simulations.
Subject
Business, Economics and Management, Human Resources and Organizations
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
