Mohammad Gholami, Director General of Smart Governance at the National Center for Cyberspace, Highlights the Critical Role of Data Governance for AI Development

Mohammad Gholami emphasized that in today’s era, falling behind in data governance inevitably leads to setbacks in artificial intelligence, potentially causing delays that could take years to recover. He made these remarks during the panel “Institutional and Legal Frameworks for Data Exchange in AI” at INOTEX 2025, stressing the urgent need for robust data governance practices.

Lack of Monitoring Mechanisms for Data Exchange Approvals

Gholami pointed out issues identified by the Interoperability Working Group, highlighting the absence of monitoring mechanisms for data exchange approvals. For example, although it was decreed that vehicle ownership data should be transferred to a private advertisement platform, there is currently no mechanism to verify that the transfer has taken place.

He further noted challenges regarding service quality, stating that legislation currently focuses on data availability but does not mandate quality standards. He suggested that agencies responsible for implementing interoperability decrees should report data outages, and penalties should be applied if services suffer reduced quality.

Structured Profiling for Agencies to Facilitate Data Exchange

Addressing security and privacy concerns, Gholami advocated for data profiling instead of blanket restrictions. By clearly defining which data can be freely exchanged and facilitating inter-agency data sharing, innovation and growth in AI and related sectors can be accelerated.

He explained that creating profiles for agencies—for instance, the Tax Administration—can define what data they can access and which portions can be released as open data, enabling private sector actors to utilize this information without additional approvals or interviews.

Citing Denmark and the Netherlands as successful models, he noted these countries have clear regulations on what data can be shared outside confidentiality levels, such as municipal data, urban services, and building permits, which can be outsourced to private platforms.

Challenges with Municipal Data and the Need for a Data Governance Document

Gholami emphasized that municipalities in Iran interact poorly when providing data, despite the potential for such data to create value and improve urban life.

He highlighted the Data Governance Document, proposed by the Ministry of Communications, which is currently being finalized. Once approved, this document is expected to fill the gaps in data exchange and management.

International Examples and Transparency Benefits

Gholami referred to successful global examples, such as Zillow in the U.S., which facilitates property transactions by profiling real estate records and reducing risks. He argued that similar data exchange frameworks could enhance technology development and business growth in Iran.

He also emphasized the role of data transparency in reducing crime, citing a judicial study where 250 fraud methods were identified through digital platforms. The Seventh National Development Plan mandates the judiciary to publish anonymized case files, which could help pinpoint sources of crime and misconduct.

Need for Better Oversight and Profiling

Finally, Gholami stressed that the Interoperability Working Group currently lacks mechanisms to monitor whether decrees for data exchange are implemented. Additionally, there is no profiling system to define what data businesses and agencies can access, highlighting the urgent need for further assessment, risk identification, and structured governance in Iran’s data exchange ecosystem.