Across the Middle East, AI has moved from a boardroom ambition to a national imperative. In the UAE and Saudi Arabia, we are witnessing a historic shift: sovereign AI stacks are being built, hyperscale compute clusters are coming online, and enterprises are moving from experimental pilots to full-scale production at breakneck speed.
However, a critical gap has emerged that could stall this momentum. Organizations are accelerating AI adoption faster than they are securing the infrastructure that powers it. According to the Cisco AI Readiness Index, only 39% of organizations in the UAE believe their current infrastructure can adequately support AI workloads.
The reality is simple: Trusted AI is impossible without a secure network. AI security is not just about the model you choose; it is about the environment in which that model lives. Trust begins at the network level, where high-quality, verifiable data is generated and acted upon in real-time.
Security Must Move with the Workload The shift to AI-native infrastructure requires a fundamental rethinking of security. Traditional “perimeter” security, inspecting traffic as it enters or leaves a network, is obsolete in an AI world. AI workloads communicate internally between distributed components; the “perimeter” is now everywhere.
Security must become part of the network fabric itself. By distributing enforcement directly onto workloads and network interface cards, security rules are created autonomously and applied at machine speed. When a GPU cluster in a regional data centre processes sensitive training data, the security travels with that data. This prevents “lateral movement,” stopping attackers from pivoting between systems before they can even begin. By embedding protection into the fabric, every packet becomes a trusted signal.
Identity: The New Continuous Perimeter In an AI-driven enterprise, the identity challenge is no longer just about humans; it’s about autonomous agents. AI agents make decisions and access systems without human oversight, creating a massive new attack surface.
We can no longer rely on static, one-time authentication. Cisco’s Unified Identity framework treats identity as a continuous conversation. By using behavioural analytics to detect when credentials are used in unexpected ways, and employing phishing-resistant multifactor authentication, we can protect against the sophisticated social engineering attacks targeting AI deployments. Every request, whether from a human or an AI agent, is evaluated in real-time based on context and risk.
Data Integrity: From Source to Decision When an AI system in a UAE hospital recommends a treatment, or a financial AI in KSA approves a high-value transaction, the data must be beyond reproach. Data integrity is not a compliance checkbox; it is the heartbeat of AI trust.
Organizations must be able to trace every data point back to its source (data lineage) and ensure it hasn’t been tampered with (provenance). By combining this with continuous model monitoring, we create an end-to-end “chain of trust” that spans from the raw data flowing across the network to the final AI output.
Defending the AI Itself As organizations embrace AI, they also face the rise of “Shadow AI”, employees using unauthorized tools that can lead to data leaks. Cisco’s AI Defense addresses this by monitoring how AI is used across the entire organization.
Beyond external threats, this technology monitors for “model drift” to ensure performance remains consistent over time and implements guardrails against “prompt injection”; attempts to manipulate AI into behaving in unintended ways. In the highly regulated environments of the Middle East, this level of control is non-negotiable.
Sovereignty and Scale Finally, we must address the physical reality of AI. AI-ready data centres must handle the massive bandwidth demands of GPU clusters without sacrificing security. For the Middle East, this also means meeting strict local data residency and sovereignty requirements. You cannot have performance at the expense of compliance; you must have both.
Start with the Network AI will reshape the economies of the Middle East, but only if the systems behind it are trusted. Trust is not a feature you add at the application layer; it is a foundation you build at the infrastructure layer.
The organizations that modernize their network foundations today will be the ones that scale AI safely, maintain regulatory confidence, and earn the lasting trust of citizens and customers. To unlock the full value of AI, we must start where the data starts: the network.
