Generative AI in Saudi Arabia – Balancing Innovation and Responsibility

Saudi Arabia’s recent Guide to Generative AI (GenAI) reflects a proactive approach to harnessing the potential of GenAI while addressing the ethical, regulatory, and societal risks associated with this transformative technology.

Released by the Saudi Data and Artificial Intelligence Authority (SDAIA), the guidelines align with Vision 2030, which aims to establish Saudi Arabia as a global leader in artificial intelligence. However, while SDAIA’s efforts are commendable, the effectiveness of these guidelines hinges on finding a balance between encouraging innovation and enforcing ethical, data-centric standards.

In this piece, I argue that Saudi Arabia’s ambitious drive to lead in GenAI requires a fine-tuned approach: one that goes beyond high-level principles to include clearer accountability mechanisms and industry-specific guidance. Without these, the Kingdom risks falling short in addressing the unique challenges of GenAI, leaving businesses uncertain and potentially vulnerable in an era of rapid AI development.

A Framework for the Future – Or a Set of Principles?

The SDAIA’s Guide to Generative AI builds on its AI Ethics Principles, covering areas such as fairness, transparency, and data privacy. These principles are both admirable and necessary, promoting the responsible design, deployment, and use of GenAI technologies. However, while they set forth a vision for ethical AI, the guidelines are currently non-binding and lack enforceability. Businesses in Saudi Arabia, therefore, face an ambiguous compliance landscape where expectations are high, yet accountability mechanisms remain minimal.

This raises a critical question: Can non-binding principles effectively govern a technology as potent and complex as GenAI? Given the pace at which GenAI is being integrated into sectors like healthcare, finance, and construction, more precise regulations are essential. Broad principles are a promising start, but they may be insufficient for addressing the nuanced risks GenAI poses, from deepfakes and misinformation to intellectual property concerns.

In my view, Saudi Arabia’s ambition to lead in AI demands regulatory evolution. The SDAIA would benefit from transforming these guidelines into enforceable standards with sector-specific rules that clarify compliance expectations and ensure consistent application across industries.

Data Privacy and Transparency – Complex Demands for GenAI

Saudi Arabia’s Personal Data Protection Law (PDPL), alongside the National Data Governance Policies, plays a pivotal role in the regulation of GenAI, especially where personal data is involved. These frameworks emphasise the importance of consent, data minimisation, and transparency. However, as GenAI models grow more sophisticated, new questions emerge around data rights and ownership. Can consent obtained for traditional data processing also apply to training AI models that generate entirely new outputs?

Transparency, a cornerstone of the SDAIA’s guidelines, is especially challenging in GenAI. With AI models that can “hallucinate” facts and create complex, human-like content, the concept of transparency needs to be redefined. It’s no longer enough for organisations to simply disclose that an AI was used; they must explain how GenAI systems work, how data is handled, and what safeguards are in place to prevent misuse.

Transparency requirements are only meaningful if paired with mechanisms that empower users to challenge and correct GenAI outputs. The risk of misinformation and reputational damage is particularly high in sectors like healthcare or legal services, where AI outputs can be taken as expert advice. Without clarity on these issues, Saudi Arabia’s data privacy protections may fall short of addressing the unique risks posed by GenAI.

Cybersecurity and IP Risks: Practical Guardrails Needed

The SDAIA has acknowledged the cybersecurity threats that GenAI presents, especially given the potential for deepfakes, data leaks, and intellectual property infringement. The Kingdom’s Essential Cybersecurity Controls and Cloud Computing Security Controls are robust frameworks aimed at protecting critical infrastructure and data security. However, applying these to GenAI may require additional, nuanced safeguards.

GenAI models, by their nature, cannot “unlearn” information, making the risk of data breaches and unintended knowledge extraction especially problematic. Businesses are left to wonder: How can we prevent GenAI from inadvertently disclosing sensitive information or replicating copyrighted material? Without clearer guidance on these points, companies are left exposed to legal and reputational risks, especially in high-stakes sectors.

The SDAIA’s guidelines should consider more specific security requirements tailored to GenAI, such as regular auditing of training datasets and stringent controls on access to AI models. Failing to address these unique security vulnerabilities could deter companies from deploying GenAI technologies, fearing regulatory backlash or potential data breaches.

Moving from Ethical Principles to Practicality

Saudi Arabia’s guide rightly highlights the need for responsible GenAI development, but the Kingdom must also consider the practical challenges that businesses face in implementing these guidelines. Ethical principles are valuable, but if they are too detached from operational realities, they risk becoming ideals rather than standards. For Saudi Arabia to become a true leader in GenAI, it must help businesses navigate these challenges with industry-specific guidance and practical, actionable standards.


1. Sector-Specific Standards: GenAI’s applications vary dramatically across industries, from financial modelling in banking to predictive diagnostics in healthcare. Each sector presents unique risks, and a one-size-fits-all approach may leave critical gaps. The SDAIA could provide sector-specific standards, helping industries adopt GenAI responsibly while addressing their specific challenges.


2. Public-Private Collaboration: The SDAIA has a unique opportunity to involve industry stakeholders in developing GenAI standards. Through partnerships and feedback loops, regulators can better understand real-world challenges and create standards that balance ethical considerations with operational feasibility. Such collaboration could help Saudi Arabia’s GenAI ecosystem grow while remaining resilient and adaptable.


3. Clear Accountability Mechanisms: Non-binding principles offer flexibility but lack the enforceability needed to ensure compliance. Saudi Arabia’s GenAI framework would benefit from clear accountability mechanisms, such as mandatory audits or penalties for serious non-compliance, creating a system where ethical AI practices are not only encouraged but required.

Conclusion: Saudi Arabia’s GenAI Future – Leading with Precision and Purpose

Saudi Arabia’s Guide to Generative AI signals a progressive and forward-thinking approach to a technology that is reshaping industries worldwide. However, the road to becoming a GenAI leader is not without its obstacles. If Saudi Arabia is to achieve its Vision 2030 ambitions, the Kingdom’s regulatory framework for GenAI must evolve from broad principles to clear, enforceable standards that guide industries while protecting individuals.

In my view, Saudi Arabia stands at a critical juncture. The Kingdom’s approach to GenAI can either foster a dynamic, ethically responsible AI ecosystem or hinder its own goals by imposing impractical standards. By refining its guidelines to include sector-specific standards, strengthening public-private collaboration, and establishing accountability mechanisms, Saudi Arabia can lead in GenAI in a way that balances innovation with ethical responsibility.

As GenAI becomes integral to our lives and economies, Saudi Arabia has the opportunity to set a global example—an example of how to embrace technology’s potential while guarding against its risks. The Kingdom’s success in this endeavour will depend on its ability to lead with precision, pragmatism, and purpose.

Contact the author
Peter Borner
Executive Chairman and Chief Trust Officer

As Co-founder, Executive Chairman and Chief Trust Officer of The Data Privacy Group, Peter Borner leverages over 30 years of expertise to drive revenue for organisations by prioritising trust. Peter shapes tailored strategies to help businesses reap the rewards of increased customer loyalty, improved reputation, and, ultimately, higher revenue. His approach provides clients with ongoing peace of mind, solidifying their foundation in the realm of digital trust.

Specialises in: Privacy & Data Governance

Peter Borner
Executive Chairman and Chief Trust Officer

As Co-founder, Executive Chairman and Chief Trust Officer of The Data Privacy Group, Peter Borner leverages over 30 years of expertise to drive revenue for organisations by prioritising trust. Peter shapes tailored strategies to help businesses reap the rewards of increased customer loyalty, improved reputation, and, ultimately, higher revenue. His approach provides clients with ongoing peace of mind, solidifying their foundation in the realm of digital trust.

Specialises in: Privacy & Data Governance

Contact Our Team Today
Your confidential, no obligation discussion awaits.