Quantitative Evaluation of the Impact of Artificial Intelligence on the Automation of Processes





Artificial intelligence, Automation, Business Processes, Operating efficiency, Quantitative Impact


Introduction: In the current era, Artificial Intelligence (AI) has profoundly transformed the operation and management of business processes, being essential for competitiveness. This article focuses on quantitatively evaluating the impact of AI on the automation of business processes, seeking to support decision making.
Objective: This study aims to carry out a quantitative evaluation of the impact of AI on business processes. Robust methods are used to measure and analyze key variables related to AI adoption.
Methods: The methodology combines secondary data and company surveys. Public business databases are accessed and financial data is collected, in addition to analyzing Key Performance Indicators (KPI). A random selection of companies is made for the surveys, a structured questionnaire is used and the data is subjected to rigorous statistical analysis.
Result: Quantitative results show significant impact of AI on business processes. The average reduction in operating costs reaches 26%, the improvement in the quality of products and services is 30%, and an average increase of 20% in profit margins is observed. Possible moderators that influence these results are identified.
Conclusion: This quantitative study supports the strategic importance of AI in business, demonstrating substantial improvements in efficiency, quality and decision making. Despite its limitations, it offers a solid framework for decision-making and future research in the field of AI and business automation.


Metrics Loading ...


Dwivedi YK, Hughes L, Ismagilova E, Aarts G, Coombs C, Crick T, et al. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manag 2021;57:101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002.

Chui M, Manyika J, Miremadi M. What AI can and can’t do (yet) for your business | McKinsey s. f. https://www.mckinsey.com/capabilities/quantumblack/our-insights/what-ai-can-and-cant-do-yet-for-your-business (accedido 1 de octubre de 2023).

Uzialko A. How Artificial Intelligence Is Transforming Business - businessnewsdaily.com. Bus News Dly s. f. https://www.businessnewsdaily.com/9402-artificial-intelligence-business-trends.html (accedido 1 de octubre de 2023).

Duan Y, Edwards JS, Dwivedi YK. Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. Int J Inf Manag 2019;48:63-71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021.

Reis J, Amorim M, Melão N, Matos P. Digital Transformation: A Literature Review and Guidelines for Future Research. En: Rocha Á, Adeli H, Reis LP, Costanzo S, editores. Trends Adv. Inf. Syst. Technol., vol. 745, Cham: Springer International Publishing; 2018, p. 411-21. https://doi.org/10.1007/978-3-319-77703-0_41.

Manyika J, Chui M, Miremadi M, Bughin J, George K, Willmott P, et al. A future that works: Automation, employment, and productivity | McKinsey s. f. https://www.mckinsey.com/featured-insights/digital-disruption/harnessing-automation-for-a-future-that-works/de-de (accedido 1 de octubre de 2023).

Benbya H, Deakin University, Melbourne, Australia, Pachidi S, Cambridge JudgeBusiness School, University of Cambridge, United Kingdom, Jarvenpaa SL, McCombs School of Business, University of Texas at Austin, U.S.A. Special Issue Editorial: Artificial Intelligence in Organizations: Implications for Information Systems Research. J Assoc Inf Syst 2021;22:281-303. https://doi.org/10.17705/1jais.00662.

Goldfarb A, Trefler D. AI and International Trade. Cambridge, MA: National Bureau of Economic Research; 2018. https://doi.org/10.3386/w24254.

Davenport TH, Kirby J. Beyond Automation. Harv Bus Rev 2015.



How to Cite

Palomino Quispe JF, Zapana Diaz D, Choque-Flores L, Castro León AL, Requis Carbajal LV, Pacherres Serquen EE, García-Huamantumba A, García-Huamantumba E, García-Huamantumba CF, Guanilo Paredes CE. Quantitative Evaluation of the Impact of Artificial Intelligence on the Automation of Processes. Data and Metadata [Internet]. 2023 Oct. 15 [cited 2023 Dec. 3];2:101. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/101