Data-Driven Strategic Management in the U.S. Industries: The Role of Management Information Systems and Artificial Intelligence

Abstract

Data-driven strategic management has emerged as a pivotal focus across industries in the United States, as organisations encounter increasing demand to transform escalating volumes of operational and market data into informed, timely, and responsible decisions. This study tackles the contemporary challenge by analysing how management information systems and artificial intelligence collaboratively facilitate strategic decision-making, resource allocation, and execution control, while also addressing a significant knowledge gap regarding why numerous firms attain experimentation without enduring scalability. The study seeks to elucidate the interaction of these two capabilities within unstable business environments and has two primary objectives: to identify the technological and managerial conditions that facilitate reliable, secure, and accountable decision support across planning, pricing, risk management, and customer operations, and to investigate how organisations develop the dynamic capabilities necessary to transition from pilot initiatives to scalable performance improvements. The study is based on the assertion that strategic value is contingent upon the alignment of data governance, system integration, workforce competency, and decision accountability, rather than on formal qualitative hypotheses. The study, framed by the resource-based view, dynamic capabilities theory, and a socio-technical systems perspective, employs a qualitative design that incorporates document analysis and interpretive synthesis of secondary evidence published from 2020 to 2026, encompassing government reports, standards guidance, peer-reviewed studies, and applied industry cases. The analysis indicates that artificial intelligence enhances strategic management just when robust information systems, high-quality data, well-defined decision rights, and effective risk governance are established. It also determines that scaling is influenced more by workflow redesign, measurement discipline, and analytic translation than by mere tool availability. The study enhances theoretical understanding by elucidating the interplay between digital resources, management reconfiguration, and governance in data-driven strategy, while also providing practical guidance for executives and policymakers aiming for responsible value generation. Given that the study is based on secondary information and concentrates on the United States, subsequent research should incorporate interviews, sector-specific case studies, and longitudinal analysis to enhance comprehension of how organisations maintain strategic advantage over time.