Building Trust in Artificial Intelligence Deployment: Designing a Trustworthy Artificial Intelligence Framework Through a Mixed Method study

Document Type : Original Article

Authors

1 Department of Management, Faculty of Management abd Accounting, Hazrat-e Masoumeh University, Qom, Iran

2 Department of Management, Faculty of Management and Accounting, Hazrat-e Masoumeh University

10.22091/jdaid.2026.16682.1087

Abstract

Objective: With the rapid expansion of artificial intelligence (AI) applications in businesses, the issue of trust in this technology has become one of the fundamental challenges in its adoption and effective utilization. A lack of sufficient trust in AI systems can lead to reduced adoption, increased risk, and weakened competitive advantage in businesses. The present study aims to provide a comprehensive and localized framework for realizing trustworthy AI in businesses.
Method: To achieve the research objective, a mixed-methods approach was adopted. In the first phase, a comprehensive literature review, together with a qualitative approach, was conducted to identify the criteria and components of trustworthy AI. During the qualitative phase, data were collected through semi-structured interviews with experts and analyzed using thematic analysis. In the second (quantitative) phase, the Best-Worst Method (BWM) was employed to prioritize and assign weights to the five main criteria and 35 identified sub-criteria. The BWM calculations were performed using LINGO software to determine the final weights.
Results:The findings showed that achieving trustworthy AI in businesses requires simultaneous attention to technical and operational, human, ethical, legal, sustainability, and social impact dimensions, among which the technical and operational aspects are the most important.
Conclusions: These results indicate that despite the rapid growth of AI in businesses, there is still no practical, localized framework in Iran that considers all these aspects in an integrated manner. Based on this, the present study presented an integrated framework for realizing trustworthy AI that can be used as a practical guide for business

Keywords

Main Subjects

References

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