General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2019 Vol.11(2): 19-22 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2019.V11.1234

Developing a Framework for Adopting Artificial Intelligence

Sanjay Mohapatra and Ajit Kumar

Abstract—Artificial Intelligence has the ability to predict outcomes accurately and with reliability. The techniques have been used in several industries and domains. However, documenting results from different research that were conducted have not been documented. Also, most of the research have been carried out in developed countries and not much work have been published from other economies. As a result, there is a need to develop proper research background so that application of AIs can be sustainable and effective. The purpose of this study is to critically review different studies that have adopted AI in several domains, so that a theoretical framework guide for researchers and practitioners can be developed. This framework will also establish future trends in the said research area. From online databases, relevant articles and extracts were retrieved and were systematically analyzed. Using these inputs, a framework was developed. The findings of this study show that there is a gap between research work done and documentation available. The present applications of AI techniques require model based approach that brings in consistency in research as well as for industry. A paradigm shift in the framework based approach could lead to achieving a sustainable practice.

Index Terms—Artificial intelligence, framework, theoretical study, AI applications.

Sanjay Mohapatra and Ajit Kumar are with Xavier Institute of Management, Bhubaneswar, India (e-mail: sanjay_mohapatra@yahoo.com, ajitmaskara@gmail.com).

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Cite:Sanjay Mohapatra and Ajit Kumar, "Developing a Framework for Adopting Artificial Intelligence," International Journal of Computer Theory and Engineering vol. 11, no. 2, pp. 19-22, 2019.


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