The Iranian Association of Islamic Finance (IAIF) convened the fourth pre-session of its 11th International Islamic Finance Conference, focusing on the application of artificial intelligence in enhancing transparency and corporate governance within the Islamic financial system. The session brought together prominent academics and industry professionals to debate whether AI represents an opportunity or a challenge in this domain.

The speakers of this session were Dr. Ali Ebrahimi Kordlar, a faculty member of the University of Tehran; Dr. Seyed Ali Hosseini, a faculty member of Alzahra University; Dr. Kaveh Mehrani, a faculty member of the University of Tehran; Dr. Haji Azimi, a lecturer at the University of Tehran; and Dr. Kalbasi, Deputy Financial Officer at Kourosh Investment Group.

Dr. Seyed Ali Hosseini opened the discussion by noting AI's profound influence on organizational decision-making structures. He emphasized the necessity of examining this technology in depth rather than superficially, given its transformative impact across various disciplines.
Dr. Ali Ebrahimi Kordlar reinforced this perspective, highlighting AI's potential to increase transparency across corporate governance components. He warned that falling behind in AI adoption would create serious challenges, stressing that transparency naturally accelerates processes. However, he cautioned that if AI is not implemented with appropriate control mechanisms, this increased speed could precipitate future crises.
The dual nature of AI as both opportunity and threat was a recurring theme. Hosseini observed that while AI can process vast data volumes with minimal error—enhancing internal audit functions, report review, and financial statement analysis—it also carries significant risks. Flawed algorithms or biased design can perpetuate errors and prejudice in organizational processes. This duality positions AI as a double-edged sword in corporate governance.
Dr. Kaveh Mehrani grounded the discussion in the fundamental relationship between transparency and accountability. He argued that without accountability, transparency becomes meaningless. Conversely, concealment or improper information disclosure misleads stakeholders and carries economic, social, and political consequences. Information manipulation, particularly in capital markets, erodes shareholder trust and damages corporate credibility.
Mehrani outlined several prerequisites for effective AI implementation. Integrated information technology infrastructure is essential; without consistent and coherent organizational data, AI may compound errors rather than resolve them. When properly deployed, AI offers three significant advantages: reduction of human error in financial judgments and classifications, enhanced fraud detection through pattern recognition, and instant transparency through real-time reporting that minimizes information asymmetry.
However, Mehrani also warned against over-reliance on AI outputs. Managers who depend solely on algorithmic recommendations without scrutinizing data quality and algorithm logic risk being misled. Furthermore, AI can be manipulated to produce desired outputs that obscure rather than illuminate truth. He advocated for legal, responsible AI use within specific regulatory frameworks.
The discussion then turned to AI's role in board decision-making. Mehrani distinguished between corporate governance's performance and supervision dimensions. In performance, AI serves as an auxiliary tool for strategy formulation and budgeting, while in supervision—particularly audit committees—AI significantly improves control quality. Hosseini raised concerns about over-reliance weakening board accountability, noting that board members must possess analytical power and the ability to challenge decisions rather than deferring to technology.
Mehrani addressed these concerns by emphasizing fundamental differences between human and artificial intelligence. Humans possess self-awareness, emotions, and accumulated experience that AI lacks. Mechanical AI use can weaken critical thinking and lead to unethical decisions. He proposed considering AI as an advisory or non-executive board member whose outputs require critique and alignment with collective wisdom. Ultimate decision-making responsibility must remain with humans.
Dr. Kalbasi identified practical challenges facing organizations in AI adoption. Information security emerged as the primary concern, as AI requires access to sensitive financial and operational data. Trust in AI systems' ability to protect data remains a significant barrier. Incomplete input data, technological infrastructure limitations, and international sanctions further complicate implementation. Kalbasi advocated for developing domestic capacities to create effective indigenous tools.
In financial applications, Kalbasi identified treasury management, accounting, auditing, and cost management as areas where AI can reduce human error and increase productivity. Timely data analysis using AI provides competitive advantages over slower human analysis. However, successful implementation requires organizational culture change, employee skill development, and gradual resistance reduction through training and experience sharing.
Haji Azimi took a critical perspective on AI in corporate governance, raising fundamental questions about legal responsibility and accountability when decisions derive from AI outputs. He warned that incomplete understanding of AI mechanisms could lead to dangerous over-reliance. While AI excels with structured data, it struggles with unstructured information based on experience and tacit knowledge. This weakness potentially undermines governance bodies' intellectual independence and shareholder trust.
Azimi identified information asymmetry as a hidden danger when only certain managers access AI algorithms while others remain unaware. He offered two key recommendations: creating structured information platforms by converting operational data into processable formats, and initially deploying AI at automation levels where risks are lower before advancing to governance applications.
In conclusion, Hosseini synthesized the discussions by highlighting AI's benefits speed, ease of big data analysis, and error reduction—alongside risks including algorithmic bias, privacy concerns, reduced human accountability, and the critical challenge of decision explainability. He emphasized that while AI adoption is inevitable, organizations must proceed with awareness, comprehensive training, and precise timing. The safe and responsible development of AI ultimately depends on continuous education and organizational preparedness.