Optimizing Target Identification in the U.S. Capital Market Mergers and Acquisitions through Artificial Intelligence: Implications for Financial Efficiency, Compliance, and National Economic Competitiveness.

Ephraim Narteh-Kofi; Emmanuel Sampson; Evans Hattoh; Rukayat Akingbade; Victor Agbeve

doi:10.36948/ijfmr.2025.v07i04.51702

Optimizing Target Identification in the U.S. Capital Market Mergers and Acquisitions through Artificial Intelligence: Implications for Financial Efficiency, Compliance, and National Economic Competitiveness.

Author(s)	Mr. Ephraim Narteh-Kofi, Mr. Emmanuel Sampson, Mr. Evans Hattoh, Ms. Rukayat Akingbade, Victor Agbeve
Country	United States
Abstract	Artificial intelligence (AI) has transformed the landscape of mergers and acquisitions (M&A) in the United States, particularly in target identification within capital markets. Notwithstanding the strategic significance of accurate target screening, traditional methods remain constrained by inefficiencies, regulatory delays, and subjective assessments. This study examines how AI technologies, including machine learning algorithms and automated analytics, are transforming the M&A process by enhancing financial efficiency, regulatory compliance, and national economic competitiveness. Using a mixed-methods approach, the research combines quantitative analysis of AI-driven M&A transactions across major U.S. financial sectors with qualitative case studies of firms implementing AI tools in target identification. The findings demonstrate that AI integration reduces transaction costs, shortens deal completion timelines, and increases the precision of valuation models. Moreover, the study also revealed that AI improves regulatory alignment through real-time compliance monitoring and predictive antitrust risk assessment. At the macroeconomic level, the paper indicated that AI adoption supports capital efficiency and strengthens U.S. firms' global positioning, contributing to national economic resilience. However, the research also identifies barriers such as legacy IT systems, data integrity issues, and the persistent need for skilled human oversight. The study, therefore, concludes that AI-driven target identification represents a technological upgrade and a paradigm shift in strategic decision-making within U.S. capital markets. Hence, successful implementation requires hybrid human-AI frameworks, investment in workforce retraining, and robust data governance. As such, AI adoption is both a competitive imperative and a public policy concern with broad implications for the future of American financial leadership.
Keywords	Artificial intelligence, mergers and acquisitions, target identification, financial efficiency, regulatory compliance, U.S. capital markets
Field	Business Administration
Published In	Volume 7, Issue 4, July-August 2025
Published On	2025-07-30
DOI	https://doi.org/10.36948/ijfmr.2025.v07i04.51702
Short DOI	https://doi.org/g9vpkp

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Optimizing Target Identification in the U.S. Capital Market Mergers and Acquisitions through Artificial Intelligence: Implications for Financial Efficiency, Compliance, and National Economic Competitiveness.

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