A study on AI's Transformative Impact on Strategic Decision-Making

Artificial intelligence (AI) is revolutionizing strategic decision-making by shifting organizations from intuition-based approaches to data-driven methodologies. It is transforming management practices, fundamentally changing how organizations develop, assess, and execute strategic decisions. This article explores AI’s profound influence across industries and examines the enabling role of AI in promoting decision accuracy, operational efficiency, and predictive intelligence across various sectors, including health care, finance, manufacturing, retail, and logistics. In healthcare, AI improves diagnostics and treatment personalization, with tools like Google’s DeepMind outperforming human radiologists. In finance, AI enhances fraud detection and algorithmic trading, as seen in Mastercard’s real-time prevention systems. AI is transforming industries by enhancing efficiency and decision-making. In manufacturing, AI-driven predictive maintenance minimizes waste and downtime, while in retail, AI is optimized for inventory management and personalized marketing strategies. In logistics, AI is leveraged for routing optimization and accurate demand forecasting. While AI offers substantial benefits, such as improved accuracy and operational efficiency, its adoption is accompanied by significant challenges, including ethical dilemmas, labor displacement, regulatory constraints, and algorithmic bias. Data privacy concerns and the high cost of implementation, particularly for smaller enterprises, complicate adoption. The article also examines how AI adoption faces significant challenges, ethical dilemmas, algorithmic bias, labor displacement, and regulatory constraints. The study emphasizes balancing AI automation with human oversight to ensure fairness, transparency, and accountability. The research advocates for responsible AI adoption, integrating ethical governance and regulatory compliance to harness AI’s potential while mitigating risks. By fostering AI-human collaboration, organizations can achieve sustainable innovation, ensuring strategic decisions are not only data-driven but also equitable and impactful across diverse industries.

Authors

Publication Details

Journal
International Journal on Science and Technology
Published
2025-06-18
DOI
https://doi.org/10.71097/ijsat.v16.i2.6335
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
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article

A study on AI's Transformative Impact on Strategic Decision-Making

Priti Bansal, Dr .Srilakshmi Ramu -
International Journal on Science and Technology
Supply Chain Resilience and Risk Management
article

A study on AI's Transformative Impact on Strategic Decision-Making

Priti Bansal, Dr .Srilakshmi Ramu -
article en

Abstract

Artificial intelligence (AI) is revolutionizing strategic decision-making by shifting organizations from intuition-based approaches to data-driven methodologies. It is transforming management practices, fundamentally changing how organizations develop, assess, and execute strategic decisions. This article explores AI’s profound influence across industries and examines the enabling role of AI in promoting decision accuracy, operational efficiency, and predictive intelligence across various sectors, including health care, finance, manufacturing, retail, and logistics. In healthcare, AI improves diagnostics and treatment personalization, with tools like Google’s DeepMind outperforming human radiologists. In finance, AI enhances fraud detection and algorithmic trading, as seen in Mastercard’s real-time prevention systems. AI is transforming industries by enhancing efficiency and decision-making. In manufacturing, AI-driven predictive maintenance minimizes waste and downtime, while in retail, AI is optimized for inventory management and personalized marketing strategies. In logistics, AI is leveraged for routing optimization and accurate demand forecasting. While AI offers substantial benefits, such as improved accuracy and operational efficiency, its adoption is accompanied by significant challenges, including ethical dilemmas, labor displacement, regulatory constraints, and algorithmic bias. Data privacy concerns and the high cost of implementation, particularly for smaller enterprises, complicate adoption. The article also examines how AI adoption faces significant challenges, ethical dilemmas, algorithmic bias, labor displacement, and regulatory constraints. The study emphasizes balancing AI automation with human oversight to ensure fairness, transparency, and accountability. The research advocates for responsible AI adoption, integrating ethical governance and regulatory compliance to harness AI’s potential while mitigating risks. By fostering AI-human collaboration, organizations can achieve sustainable innovation, ensuring strategic decisions are not only data-driven but also equitable and impactful across diverse industries.

International Journal on Science and TechnologyVol. 16(2)
Industry, innovation and infrastructure
Openalex Percentile: Top 79%
Supply Chain Resilience and Risk Management
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