The UAE’s plan to shift 50% of government services to AI within the next two years is one of the most ambitious public sector transformations underway anywhere in the world. But the real story is not the scale of that ambition. It is what happens next.

by Samir Akel, Regional VP, Emerging Markets, Nintex

Across both government and enterprise, we are seeing a shift from AI as a tool that supports decisions, to AI as a system that can execute them. This is where agentic AI comes into focus, moving beyond prompts and outputs towards systems that can understand intent, plan actions, and complete tasks across multiple environments. In theory, this approach could change everything. However, in practice, it introduces a new level of complexity. 

Why agentic AI needs orchestration

Government services are not standalone processes. They span ministries, data environments, regulatory frameworks, and legacy systems, all of which need to operate with precision, auditability, and control. Introducing AI into that environment is not simply a question of capability, it is a question of coordination.

This is why the next phase of AI adoption will not be defined by models alone. It will be defined by orchestration. 

Agentic AI depends on the ability to operate across interconnected systems in a structured way. Without that, autonomy quickly becomes fragmentation. Tasks may be automated in isolation, but end-to-end execution remains out of reach. 

Orchestration provides the layer that connects these systems, defining how workflows are designed, how decisions are made, and how processes are governed. It ensures that AI operates within clear parameters, with visibility over how actions are taken and outcomes are achieved. 

Control, governance, and the role of infrastructure

For governments, having control is critical. Public sector processes demand a higher standard of accountability than most enterprise environments. Decisions must be explainable. Data must remain secure. Outcomes must be consistent and compliant across a wide range of use cases, from licensing and healthcare to immigration and business registration. 

Technologies such as the newly launched business organisation platform Nintex K2 are designed to give organisations control over how workflows are built and managed, enabling them to embed AI into processes in a way that aligns with existing governance frameworks. This includes integrating across legacy and modern systems, embedding compliance directly into workflows, and ensuring accessibility across diverse user groups. 

Recent developments, including the introduction of locally hosted AI capabilities, reflect a broader shift in how organisations are approaching AI adoption. Rather than relying entirely on external services, there is growing demand for models that can operate within trusted environments, maintaining full control over data and decision-making. In highly regulated contexts, this is not simply a preference, it is an absolute requirement. 

What this means for the UAE

The UAE has already invested heavily in the infrastructure needed to support connected, digital-first government services. The next step is to move beyond digitisation towards execution, where systems do not simply respond to requests but complete them, essentially agentic government. 

For residents, it means a fundamental shift in how services are experienced. Processes such as visa renewals, licence applications, or business registrations could move from multi-step interactions across different platforms to a single request, with the underlying complexity handled automatically. 

For governments, the impact is equally significant. AI-enabled workflows can support faster decision-making, more efficient resource allocation, and greater consistency across services. It also creates the foundation for more proactive service delivery, where systems anticipate needs rather than waiting for requests. 

Designing for accountability from the outset

However, realising the UAE’s vision depends on more than deploying AI at scale. It requires a deliberate approach to how these systems are designed, governed, and integrated. As AI takes on greater responsibility for executing tasks, questions around oversight, accountability, and control become central to the conversation.

Where should human intervention remain? How are automated decisions audited? How can organisations ensure that AI-driven processes remain transparent and aligned with regulatory requirements? These are not challenges that can be addressed after the fact. They need to be built into the architecture from the outset.

A blueprint for global AI adoption

This is why the UAE’s approach is so significant. By focusing not just on AI adoption but on how AI is operationalised, there is an opportunity to set a new benchmark for what large-scale, real-world AI deployment looks like, one that balances speed with structure, and innovation with control.

As global economic and geopolitical pressures continue to reshape national priorities, countries are accelerating efforts to diversify beyond traditional revenue models, and invest in digital infrastructure as a foundation for long-term growth. The UAE is no different, with recent times making this even more of a priority. In this context, AI is not just a technology play, it is becoming a core component of the nation’s capabilities to remain competitive on the international stage. 

If orchestration is placed at the centre of this transformation, AI can move from isolated use cases to fully integrated execution. Services become faster, more intuitive, and more resilient. If the UAE gets this right, it will not only accelerate its own transformation. It will provide a blueprint for how governments around the world can move from AI ambition to operational reality.