The Economic Footprint of AI: A Systematic Review of Business and Development Literature

Munshi Naser Ibne Afzal and Tahir Masood Qureshi

International Journal of Economics & Business Administration (IJEBA), 2025, vol. XIII, issue 2, 92-107

Abstract: Purpose: This study advances AI research by mapping its economic footprint, offering practical insights for businesses, and proposing ethical policy solutions. It aligns with Discover Artificial Intelligence’s mission to foster responsible AI innovation for societal benefit. Design/Methodology/Approach: This systematic literature review (SLR), adhering to PRISMA guidelines, synthesizes 85 peer-reviewed studies from 2015 to 2024, sourced from Scopus, Web of Science, and Google Scholar, to explore AI’s applications, impacts, and challenges in business, economics, finance, and accounting. Findings: Research gaps include limited studies on small and medium enterprises (SMEs) and robust AI governance frameworks. Findings from this research highlight AI’s strengths in process automation, predictive analytics, and customer engagement, alongside challenges like ethical biases, skill shortages, and uneven adoption. Practical Implications: Artificial Intelligence (AI), powered by big data, is reshaping business and economic landscapes through advanced analytics, automation, and innovation. Originality value: Artificial Intelligence, Business Analytics, Big Data, Economics, Ethical AI, Systematic Review, Economic Development

Keywords: Artificial Intelligence; business analytics; Big Data; economics; ethical AI; systematic review; economic development. (search for similar items in EconPapers)
JEL-codes: F63 L86 M15 O14 O33 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijeba.com/journal/885/download (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ers:ijebaa:v:xiii:y:2025:i:2:p:92-107

Access Statistics for this article

More articles in International Journal of Economics & Business Administration (IJEBA) from International Journal of Economics & Business Administration (IJEBA)
Bibliographic data for series maintained by Marios Agiomavritis ().