Generative AI in Strategic Business Planning: Boosting Efficiency and Competitive Advantage in Business Organizations

Aim: This study investigates the application of generative AI in strategic business planning, with a particular focus on its potential to enhance operational efficiency and economic competitiveness in businesses organizations. Problem Statement: Before the advent of generative AI, businesses relied on traditional methods for routine tasks, business planning, and decision-making. These methods were often associated with significant challenges that hindered overall business efficiency. Significance of the Study: The application of generative AI plays a vital role in strategic planning and decision making of businesses. Recently, generative AI has transformed from a revolutionary concept to a transformative dynamism across various industries. This technology has shown incomparable competences in all ways. Methodology: This review article is based on an analysis of information gathered from high-impact journal publications. Discussion: This study critically examines the role of AI in strategic business planning and the techniques required for its effective implementation. Generative AI enhances competitiveness by facilitating product development and innovation, optimizing sales and marketing strategies, and enabling data-driven decision-making. However, several challenges must be addressed, including legal and ethical considerations, implementation and integration hurdles, and the need for continuous adaptation and learning. The future of generative AI in strategic business decisions is expected to include advancements in AI technologies, increased collaboration between AI and human intelligence, industry-specific AI applications, and the development of ethical AI governance frameworks. Businesses that integrate AI technologies—such as operational optimization, personalized customer interactions, and predictive analytics—stand to achieve significant improvements in customer satisfaction, innovation, and overall efficiency. Conclusion: The application of generative AI has demonstrated a positive impact on strategic business planning and has proven essential for businesses striving to remain competitive in dynamic markets. However, addressing the associated challenges is imperative to ensure the successful implementation and integration of AI into business strategies for sustainable growth and decision-making.

Authors

Institutions

Publication Details

Journal
Asian Journal of Economics Business and Accounting
Published
2025-02-28
DOI
https://doi.org/10.9734/ajeba/2025/v25i31695
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI in Strategic Business Planning: Boosting Efficiency and Competitive Advantage in Business Organizations

Lauret Kambili Maduka
1 citations
Asian Journal of Economics Business and Accounting
Big Data and Business Intelligence
2.28
article

Generative AI in Strategic Business Planning: Boosting Efficiency and Competitive Advantage in Business Organizations

Lauret Kambili Maduka
article en
1 citations

Abstract

Aim: This study investigates the application of generative AI in strategic business planning, with a particular focus on its potential to enhance operational efficiency and economic competitiveness in businesses organizations. Problem Statement: Before the advent of generative AI, businesses relied on traditional methods for routine tasks, business planning, and decision-making. These methods were often associated with significant challenges that hindered overall business efficiency. Significance of the Study: The application of generative AI plays a vital role in strategic planning and decision making of businesses. Recently, generative AI has transformed from a revolutionary concept to a transformative dynamism across various industries. This technology has shown incomparable competences in all ways. Methodology: This review article is based on an analysis of information gathered from high-impact journal publications. Discussion: This study critically examines the role of AI in strategic business planning and the techniques required for its effective implementation. Generative AI enhances competitiveness by facilitating product development and innovation, optimizing sales and marketing strategies, and enabling data-driven decision-making. However, several challenges must be addressed, including legal and ethical considerations, implementation and integration hurdles, and the need for continuous adaptation and learning. The future of generative AI in strategic business decisions is expected to include advancements in AI technologies, increased collaboration between AI and human intelligence, industry-specific AI applications, and the development of ethical AI governance frameworks. Businesses that integrate AI technologies—such as operational optimization, personalized customer interactions, and predictive analytics—stand to achieve significant improvements in customer satisfaction, innovation, and overall efficiency. Conclusion: The application of generative AI has demonstrated a positive impact on strategic business planning and has proven essential for businesses striving to remain competitive in dynamic markets. However, addressing the associated challenges is imperative to ensure the successful implementation and integration of AI into business strategies for sustainable growth and decision-making.

Asian Journal of Economics Business and AccountingVol. 25(3)
Arizona State University (US)
Openalex Percentile: Top 14%
Big Data and Business Intelligence
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.