Evaluating the Capability of Selected Iranian Organizations for Joint Human-Al Decision-Making: A Shannon Entropy-COPRAS Approach

The rapid development of artificial intelligence has transformed organizational decision-making by enabling data-driven analysis, prediction, automation, and intelligent decision support. However, the effectiveness of AI in organizations depends not only on technological infrastructure, but also on the ability of humans and AI systems to collaborate in a transparent, responsible, and value-creating manner. Accordingly, this study aims to evaluate the capability of selected Iranian organizations for joint human-AI decision-making using a multi-criteria decision-making approach. The research is applied in terms of purpose and descriptive-analytical in terms of method. Data were collected through a structured expert questionnaire completed by ۱۲ experts in artificial intelligence, digital transformation, organizational decision-making, data analytics, and multi-criteria decision-making. The Shannon Entropy method was used to determine the objective weights of the evaluation criteria, and the COPRAS method was applied to rank the selected organizations. The results showed that AI governance, ethics, and accountability had the highest weight among the criteria, followed by implementation risk and organizational resistance. These findings indicate that organizational capability for joint human-AI decision-making is shaped not only by data quality and technological infrastructure, but also by governance maturity, ethical responsibility, explainability, employee readiness, and risk management. The COPRAS results showed that Fanap Holding ranked first, followed by Snapp Group, Bank Mellat, Digikala Group, and Tapsi. The findings suggest that AI readiness should be treated as a socio-technical capability. Organizations need reliable data and AI infrastructure, but they also need clear governance rules, trained employees, human oversight, and mechanisms for managing resistance.

کلیدواژه ها:

Artificial intelligence ، human-AI collaboration ، organizational capability ، joint decision- making ، Shannon Entropy ، COPRAS ، multi-criteria decision-making