IDEAS home Printed from https://ideas.repec.org/a/air/journl/v12y2025i5p705.html

Artificial Intelligence Applications and Global Economic Performance: An Empirical Investigation

Author

Listed:
  • Leonard Amaefule
  • Sylvester Durukwuaku

Abstract

The main objective of this study is to investigate the association between Artificial Intelligence (AI) and global economic performance. The study specifically evaluated the relationship between the Global Total Corporate Artificial Intelligence Investment (GTCAII), as proxy for AI, and the proxies of global economic performance, namely; World’s Gross Domestic Product Growth Rate (WGDPGR), World Inflation Rate (WInR), World Unemployment Rate (WUnR) and World Manufacturing Output (WMO). Data were sourced from World Bank publications and Mamcrotrends for periods of 2013-2022; Descriptive statistics alongside ordinary least square regression analysis were employed to analyze the data collected. Findings from the analysis revealed that within the period covered in the study, GTCAII showed negative but insignificant relationship with WGDPGR and WInR; positive but insignificant association with WUnR and WMO. The study thus concluded that the application of AI in the global productive and other economic activities so far, has not shown any indication of significant effect on global economic performance. The implication of the findings is that so far, the total corporate investments in artificial intelligence equipment have not significantly spurred economic performance across world economies, in terms of gross domestic product growth rate, inflation rate, unemployment rate and manufacturing outputs.

Suggested Citation

Handle: RePEc:air:journl:v:12:y:2025:i:5:p:705
DOI: 10.5281/zenodo.15622126
as

Download full text from publisher

File URL: https://www.ijmae.com/article_222289_45bd54e6bd9f48327b39a6c08eb9d529.pdf
Download Restriction: no
File URL: https://libkey.io/10.5281/zenodo.15622126?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;
;
;
;

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:air:journl:v:12:y:2025:i:5:p:705. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Behzad Hassannezhad Kashani (email available below). General contact details of provider: https://www.ijmae.com/ .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.