An Intelligent Decision Support Framework Integrating Artificial Intelligence, Computer Information Systems, and Management Analytics for Industry

Authors

  • Nayani Sateesh Department of Computer Science and Engineering, CVR College of Engineering, Hyderabad, Telangana, India.
  • Mohammed Zabeeulla A. N. Department of Computer Science and Information Technology, JAIN (Deemed-to-be University), Bengaluru, Karnataka, India.
  • Alok Kumar Bhargava The Inner Engine Framework™ for Conscious Leadership Assessment; Author of The Inner Engine of Leadership Trilogy; TrayiVani Foundation, Ghaziabad – 201016, Uttar Pradesh, India.
  • Harsimran Singh Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India. Specialization: Machine Learning, Wireless Networking and IoT.
  • Uttam Mande Department of Computer Science and Engineering, Raghu Engineering College, Visakhapatnam, Andhra Pradesh, India.
  • Sammy Mande Research Department, Shamgar Software Solutions.

DOI:

https://doi.org/10.70917/ijcisim-2026-3164

Keywords:

Artificial Intelligence, Computer Information Systems, Management Analytics, Intelligent Decision Support, Industry 4.0, Digital Transformation, Business Analytics, Industrial Performance, Decision Support Systems

Abstract

Background: The rapid changes of Industry 4.0 and Digital Transformation have indeed accelerated the use of Artificial Intelligence (AI), Computer Information Systems (CIS) and Management Analytics (MA) in the industrial sectors. While these technologies have helped to enhance operational efficiency, organizational performance and evidence-based decision making, they have not been well integrated. Therefore, it is essential to have an integrated approach that integrates these complementary technologies to assist intelligent industrial decision-making. 
Objective: This systematic review is designed to condense the available literature on the incorporation of Artificial Intelligence, Computer Information Systems, and Management Analytics in industrial settings, spot the latest patterns and hurdles in research, and suggest an Integrated Intelligent Decision Support Framework (IIDSF) for industries in India. 
Methods: The review was carried out with the PRISMA 2020 guidelines. A comprehensive literature search was conducted in Scopus, Web of Science, IEEE Xplore, ScienceDirect, SpringerLink, ACM Digital Library, Emerald Insight, Taylor & Francis Online, Google Scholar, and ProQuest, as well as relevant government and industrial reports. A search of published studies in English from January 2010 to June 2026 was conducted with a set of inclusion and exclusion criteria. Studies were systematically analysed using a qualitative narrative synthesis. 
Conclusions: The suggested framework provides a holistic conceptual framework for the integration of Artificial Intelligence, Computer Information Systems, and Management Analytics to improve intelligent decision making, operational efficiency, and sustainable performance of industries. It gives a good starting point for future empirical research and also gives practical suggestions to organizations which want to speed up the rate of digital transformation and enhance the industrial competitiveness in India.

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Published

2026-07-14

How to Cite

Nayani Sateesh, Mohammed Zabeeulla A. N., Alok Kumar Bhargava, Harsimran Singh, Uttam Mande, & Sammy Mande. (2026). An Intelligent Decision Support Framework Integrating Artificial Intelligence, Computer Information Systems, and Management Analytics for Industry. International Journal of Computer Information Systems and Industrial Management Applications, 18(7s), 932–943. https://doi.org/10.70917/ijcisim-2026-3164

Issue

Vol. 18 No. 7s (2026)

Section

Original Articles