Maan Al-Shakarchi, Regional Director, META, Extreme Networks, on what the UAE’s agentic AI vision means for the rise of autonomous enterprise networks.

The UAE has never been afraid to set ambitious technology goals, and its latest move may prove to be one of its most transformative.

The country recently became the first in the world to launch a national agentic AI initiative, setting out a vision to embed autonomous AI across government operations. Dubai has since extended that ambition into the private sector, encouraging businesses to embrace agentic AI as a catalyst for innovation and economic growth. With PwC estimating that AI could contribute almost US$96 billion to the UAE economy by 2030, representing nearly 14% of GDP, the country’s direction of travel is unmistakable.

For enterprises, this is no longer a question of whether to adopt agentic AI, but how to do so in a way that delivers measurable business outcomes. Organisations that begin with focused, high-value use cases will be better placed to develop the infrastructure, governance and operational frameworks required to scale AI responsibly over time.

Moving from AI assistance to autonomous action

As agentic AI moves beyond experimentation and into mainstream enterprise adoption, organisations should focus on practical deployments that solve real business challenges.

According to Gartner, by 2028 one-third of enterprise software applications will incorporate agentic AI capabilities, up from less than 1% in 2024. This rapid acceleration means organisations must demonstrate tangible business value early while building confidence in AI-enabled operations.

Enterprise networking represents one of the most compelling environments in which to realise that value. Networks generate enormous volumes of real-time operational data, underpin mission-critical services and support many repetitive yet business-critical processes that are well suited to intelligent automation.

Rather than relying on IT teams to identify and resolve issues manually, agentic AI can continuously analyse network conditions, surface contextual recommendations and, where appropriate, take autonomous action within clearly defined governance policies. For example, it could detect growing Wi-Fi congestion in a school and automatically rebalance traffic, or identify recurring point-of-sale performance issues in a retail environment and prioritise business-critical applications during peak trading periods.

This represents a shift from AI acting purely as an assistant to AI becoming an active operational participant capable of improving network performance in real time.

Intelligent infrastructure will underpin the agentic AI era

The success of agentic AI will depend as much on the underlying network infrastructure as on the AI applications themselves.

Traditional enterprise networks were designed for predictable workloads and relatively static environments. Agentic AI introduces continuous data processing, autonomous decision-making and dynamic interactions across applications, devices and users. Supporting these new operating models requires networks that are intelligent, resilient and capable of providing real-time visibility across increasingly complex environments.

This fundamentally changes the role of enterprise networking.

Rather than simply connecting people, applications and devices, the network becomes an active source of operational intelligence. It provides the context AI systems need to make informed decisions, while enforcing the governance, security and policy controls that ensure autonomous agents operate safely and transparently.

As organisations deploy increasing numbers of AI agents across the enterprise, networks will also become central to identity management, access control and auditability, ensuring every autonomous action remains visible, traceable and aligned with business policy.

In many respects, the relationship is becoming mutually reinforcing. Networks provide the intelligence that enables AI, while AI continuously enhances the performance, resilience and efficiency of the network itself.

The demands on enterprise infrastructure are already becoming apparent. Recent research shows that 92% of technology leaders believe AI is increasing pressure on computing resources and network bandwidth. Organisations that modernise their infrastructure today will therefore be significantly better positioned to support increasingly autonomous business operations in the years ahead.

Human expertise remains indispensable

While AI systems are becoming more capable, their success will continue to depend on people.

Agentic AI is not about replacing skilled professionals. Instead, it enables them to focus on higher-value activities by reducing the burden of repetitive operational tasks.

Within IT, this means engineers can spend less time responding to routine incidents and more time developing strategy, improving resilience and driving innovation. Human judgement remains essential for governance, oversight and accountability, particularly as organisations entrust AI with increasingly important operational responsibilities.

This evolution also requires investment in skills.

The World Economic Forum’s Future of Jobs Report identifies AI as one of the primary drivers of workforce transformation over the coming decade, highlighting the need for widespread reskilling and upskilling across industries.

Preparing employees to work effectively alongside AI-powered systems will become just as important as investing in the technology itself. Organisations that combine intelligent automation with a highly skilled workforce and strong governance frameworks will be best placed to unlock the full value of agentic AI.

Preparing for an autonomous future

The UAE has made its ambitions clear. Agentic AI is rapidly moving from strategic vision to operational reality.

For enterprises, the next phase of AI adoption will not simply involve deploying intelligent applications. It will require building the intelligent infrastructure capable of supporting them securely, reliably and at scale.

Enterprise networks are evolving into the foundation upon which autonomous operations will depend, providing the visibility, intelligence and control needed for AI-driven decision-making.

Organisations that recognise this shift early, invest in modern network infrastructure and prepare their people for a more autonomous future will be best positioned to realise the long-term value of agentic AI and compete in an increasingly AI-driven economy.