The United Arab Emirates (UAE) has long pursued a vision of becoming a global leader in artificial intelligence, and recent developments indicate the nation is moving beyond pilot projects toward full-scale deployment of autonomous, agentic systems. This strategic shift, while ambitious, brings to the forefront critical questions around governance, accountability, and security. As government agencies across the Gulf Cooperation Council (GCC) prepare to integrate AI more deeply into public services, experts warn that the gap between high-level strategy and day-to-day operational execution must be closed to ensure responsible innovation.

The strategic foundation: UAE’s AI ambitions

The UAE’s commitment to AI is not new. Under the UAE Strategy for Artificial Intelligence 2031, the government established a Ministry of Artificial Intelligence in 2017, making it one of the first countries in the world to create a dedicated AI ministry. This was followed by the launch of the UAE AI Ethics Guidelines in 2021, which laid out principles for responsible AI development. More recently, the UAE announced plans to transition a significant portion of government services to autonomous, agentic AI models within the next two years. This marks a fundamental shift from using AI as a support tool to positioning it as an active decision-making and execution layer capable of analyzing data, making recommendations, and carrying out actions in real time.

Agentic AI differs from traditional AI because it can autonomously perform tasks, coordinate workflows, and make decisions within predefined boundaries. Potential applications include automated citizen services, regulatory supervision, intelligent case management, and smart infrastructure operations. For instance, an agentic AI system could autonomously process visa applications, monitor traffic systems, or manage emergency response coordination. As highlighted by Aben Pagar, head of digital risk consulting at Konexo, the UAE has set the pace in terms of ambition, but operationalizing governance frameworks remains a challenge.

Governance gap: Between policy and practice

While GCC governments have been praised for their visionary AI strategies and rapid adoption programs, many organisations still struggle to bridge the gap between strategy and execution. Pagar notes that governance frameworks are often well-articulated at a strategic level but are still maturing in how they are embedded into day-to-day operations and system design. This gap becomes more visible as governments move beyond pilots into production environments. Accountability is becoming a central concern, especially as AI systems increasingly take on roles that were previously performed by humans. Each AI system should have a clearly designated owner responsible for its performance, risks, and compliance throughout its lifecycle, Pagar argues. Decisions influenced by AI must be explainable and, where necessary, challengeable.

Nasser Ali Khasawneh, global head of technology and digital sector at Eversheds Sutherland, points out that GCC countries have been among the first to create central AI bodies or ministries with clearly defined remits over AI strategy. These institutions will play an increasingly important role as governments seek to scale AI adoption while maintaining oversight. As this transition unfolds, governance frameworks will need to evolve accordingly, with clearer expectations on how controls are applied in practice. The UAE, for example, could expand its risk-based implementation models to incorporate real-time monitoring and auditing of AI systems.

Data governance and cybersecurity: The new backbone

The shift towards agentic AI elevates the importance of data governance. Data protection will increasingly form the backbone of AI governance, particularly around data quality, consent, and cross-border considerations, says Pagar. At the same time, transparency and explainability become more critical as AI plays a more active role in decision-making. Cyber risk now extends beyond infrastructure into the models themselves, including risks such as manipulation, misuse, and unintended behavior. Security is becoming an integral part of AI design and governance, not an afterthought.

Data residency requirements are influencing architecture choices, supplier selection, and deployment models. For public sector organisations in the UAE, ensuring that data remains within national borders while leveraging global AI capabilities presents a complex challenge. The UAE’s regulatory framework, including the Federal Decree-Law No. 45 of 2021 on the Protection of Personal Data, sets standards that must be integrated into AI systems. As agentic AI systems become more autonomous, they will require robust data governance mechanisms to prevent bias, ensure fairness, and maintain compliance with local and international regulations.

Scaling responsibly: Embedding governance into the lifecycle

For public sector organisations looking to move AI projects from experimentation into production, governance must be embedded directly into systems and processes. The key is to treat governance not as a separate compliance layer but as an integral part of the AI lifecycle. This starts with establishing clear visibility over where AI is being used across the organization, followed by risk classification based on impact and sensitivity. Pagar emphasizes that organisations should implement continuous monitoring and validation processes to ensure AI systems remain aligned with ethical guidelines and legal requirements.

The UAE’s ambitions are clear, but the primary challenge is not identifying use cases—it is scaling them responsibly. Integration with legacy systems, maintaining transparency in decision-making, and building public trust are all critical. Public trust, in particular, hinges on citizens’ ability to understand and contest automated decisions. If a government AI system denies a service or flags a security threat, there must be a clear mechanism for human review and redress. As the UAE pushes towards agentic AI, it will need to invest in public education and engagement to build confidence in these technologies.

Regional context: GCC peers and global comparisons

The UAE is not alone in its pursuit of AI-driven governance. Saudi Arabia launched its National Strategy for Data and AI in 2020 and created the Saudi Authority for Data and Artificial Intelligence (SDAIA). Qatar has its own National AI Strategy, while Oman and Bahrain are developing frameworks for AI adoption. What sets the UAE apart is its pace and ambition, particularly the goal of transitioning to agentic AI within two years. However, experts caution that speed must not come at the expense of safeguards. Other GCC countries are watching closely, and the UAE’s success or failure could shape regional AI governance standards.

Globally, the UAE’s approach offers lessons for both developed and developing nations. While the European Union’s AI Act takes a prescriptive, risk-based approach, the UAE’s model is more agile and top-down. This allows for rapid deployment but risks regulatory gaps. The UAE’s focus on agentic AI may push other nations to accelerate their own governance reforms, particularly around accountability for autonomous decisions.

Looking ahead: From experimentation to disciplined execution

The next few years will be decisive for the UAE’s AI transformation. As government agencies adopt agentic AI at scale, the demand for skilled professionals in AI governance, cybersecurity, and data ethics will grow. Universities and training programs must adapt to prepare the workforce. The private sector, too, will play a role—technology vendors and consultants will need to provide tools for explainability, auditing, and risk management. Ultimately, success will depend on the ability to move from experimentation to disciplined, scalable execution. In this environment, effective AI governance becomes a key enabler, ensuring that innovation is delivered with confidence, accountability, and long-term sustainability.

The UAE’s push into agentic AI is a bold step that could redefine public service delivery in the region. But without robust governance frameworks, the risks of bias, misuse, and loss of public trust loom large. As Pagar notes, the ambition is clear, but the primary challenge is scaling responsibly. The UAE has a historic opportunity to set a global benchmark for responsible autonomous AI in government—provided it can translate its strategic vision into operational reality.

Source: ComputerWeekly.com News