Identification and Prioritization of Key Requirements for Artificial Intelligence Intermediary Firms in the Innovation Ecosystem (Case Study: Mining and Metallurgical Industries)

Boshrouei Shargh, Setareh; Khosropour, Hossein; Khaledi, Arman

doi:10.22034/imj.2026.586578.2991

Identification and Prioritization of Key Requirements for Artificial Intelligence Intermediary Firms in the Innovation Ecosystem (Case Study: Mining and Metallurgical Industries)

Document Type : Original Article

Authors

Setareh Boshrouei Shargh ¹

Hossein Khosropour ²

Arman khaledi ³

¹ Researcher, Technology Studies Institute, Tehran, Iran

² Department of Technology Management and Entrepreneurship, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran

³ Assistant Professor of Science and Technology Policymaking, Innovation Policy and Foresight Group, Technology Studies Institute

10.22034/imj.2026.586578.2991

Abstract

With the expansion of artificial intelligence and the gradual shift in countries’ focus from algorithm development to organizational deployment, the importance of institutions that act as intermediaries between technology, innovation ecosystem actors, and market needs has increased. “AI intermediary firms” are among such institutions and require structural, institutional, technical, and technological requirements to effectively fulfill their role in AI utilization. This study aims to identify and prioritize these requirements within the innovation ecosystem of mining industries. In the first stage, a preliminary list of requirements was extracted through a review of the literature and analysis of relevant policy documents, and then organized into conceptual dimensions. These dimensions were refined and finalized based on expert opinions in artificial intelligence and innovation. In the quantitative phase, the final requirements were prioritized using experts’ ordinal judgments, and agreement levels and ranking differences were examined. The findings indicate that all extracted dimensions are statistically significant. The highest agreement is associated with human capital and key expertise, business models and investment, and technical and operational infrastructure, whereas commercial capabilities and business development show the lowest consensus. The results provide an integrated view of the formation and performance requirements of AI intermediary firms and can serve as a basis for policymakers and managers to strengthen capacity building, facilitate technology utilization, and improve AI governance.

Keywords

Artificial Intelligence

AI Intermediary Firms

Innovation Ecosystem

Intermediary Organizations

Multi-Criteria Decision-Making (MCDM)

Subjects