Business Intelligence Management Studies

Foresight of Artificial Intelligence Applications in Banks Based on Business Intelligence Maturity: A Scenario Planning Approach

Document Type : Research Paper

Authors

Arash Ghashami 1
Mahmood Alborzi 2
Farzad Movahedi Sobhani 3
Reza Radfar 4

1 Ph.D. Candidate in Information Technology Management, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, IranCorresponding Author: mahmood_alborzi@yahoo.com

3 Assistant Professor, Department of Industrial Engineering, Science and Research Unit, Islamic Azad University, Tehran, Iran.

4 Professor, Department of Industrial Management and Accounting, Science and Research Branch, Islamic Azad University, Tehran, Iran

https://doi.org/10.22054/ims.2025.86249.2628
Abstract
The success of artificial intelligence (AI) deployment in any organization depends on the success of its business intelligence (BI) systems. This research aims to identify the main scenarios for the development of AI-based banking in the country's banks, based on their success in implementing BI systems. The existing research gap arises because current theoretical knowledge cannot explain the failure of AI projects in banks. To formulate these scenarios, a literature review was conducted to extract 32 drivers from the dimensions of BI maturity, whose positive impacts on the successful development of AI applications had been proven in previous studies. The most prioritized of these drivers were then examined by experts from 12 banks that had experience with both BI system deployment and AI-based banking development programs. This was done using a questionnaire and the Fuzzy Delphi technique. In the first stage, 10 drivers were selected, weighted, and normalized using the COPRAS method, and two drivers were chosen from among them: data quality and the level of data and systems integration. Using these two drivers, four future scenarios were formulated. To identify the most probable scenario, the MABAC technique was employed, and experts predicted the likelihood of each scenario based on the BI maturity scores of their respective banks, using the distance from similarity boundary technique. The main finding of the research is that banks are at risk of Costly and Irretrievable Intelligence in the development of AI applications

Keywords

Artificial Intelligence
Business Intelligence Maturity
Foresight
Scenario Planning
Subjects

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    ‌ ‌استناد به این مقاله: قشمی، آرش.، البرزی، محمود.، رادفر، رضا.، موحدی سبحانی، فرزاد.. (1404). آینده‌نگاری کاربرد هوش مصنوعی در بانک‌ها با توجه به میزان بلوغ هوشمندی کسب و کار از طریق رویکرد سناریونگاری، مطالعات مدیریت کسب وکار هوشمند، 14(54)، 121-174. DOI: 10.22054/ims.2025.86249.2628

     Journal of Business Intelligence Management Studies is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License..

Business Intelligence Management Studies
Volume 14, Issue 54
Autumn 2026
Pages 121-174

  • Receive Date 07 June 2025
  • Revise Date 16 September 2025
  • Accept Date 20 September 2025

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