Identifying and ranking the drivers for improving and developing the application of artificial intelligence in the Iranian oil and gas industry value chain

Document Type : Original Article

Authors

1 Master of Public Administration, Faculty of Management and Accounting, Allameh Tabatabaei University, Tehran, Iran.

2 Associate Professor, Department of Business Administration, Faculty of Management and Accounting, Allameh Tabatabai University, Tehran, Iran.

3 Master of Business Administration, School of Management, University of Tehran, Tehran, Iran.

Abstract

Background and Objectives: Today, artificial intelligence technology, by focusing on algorithms based on the intelligentization of operational processes with more accurate risk prediction and preventive maintenance, increases safety and reduces sudden stops in production and transmission processes in the value chain of the oil and gas industry. Therefore, the purpose of this research was to identify and rank the drivers of improvement and development of the application of artificial intelligence in the value chain of the oil and gas industry in the Republic of Iran.
Materials and Methods: In terms of the method of conduct, the present study is based on structural interaction matrix analysis with a strategic futures research approach and in terms of the purpose, it is of a developmental-applied type. The statistical population of this study consists of 30 academic experts and senior managers of the oil and gas industry in the Republic of Iran. The data of this study were collected through library studies, structured interviews, and a qualitative questionnaire rated from zero to three according to the structural interaction matrix and analyzed with the MICMAC statistical software.
Results: The findings of this study showed that the drivers of improving interaction and cooperation between IT units and operational and strategic departments, attracting, training and developing human resources specialized in the fields of artificial intelligence and oil and gas engineering, and establishing the ability to integrate smart systems with operational processes and equipment in the industry are influential drivers (influence).
Conclusion: The results of this study showed that identifying and ranking the drivers of improvement and development of the application of artificial intelligence in the value chain of the Iranian oil and gas industry with a strategic futures research approach can pave the way for identifying upcoming opportunities and threats.

Keywords

References

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Strategic Value Chain Management
Volume 2, Issue 1 - Serial Number 4
Research papers
May 2025
Pages 59-85

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History

  • Receive Date: 23 July 2025
  • Revise Date: 05 August 2025
  • Accept Date: 12 August 2025
  • Publish Date: 22 May 2025

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