As AI investment accelerates across the Gulf, service providers are facing a critical inflection point. Governments and enterprises in the UAE and Saudi Arabia are pouring capital into AI models, data centers, and sovereign digital infrastructure, with projected economic impact exceeding USD 320 billion by 2030. Yet amid this momentum, one constraint is becoming increasingly clear: AI ambitions are advancing faster than network readiness.
The success of AI at scale depends less on models themselves and more on the networks that connect, secure, and sustain them. While AI pilots often perform well in controlled environments, many struggle to move into production due to latency, bandwidth, and performance consistency issues — challenges that are fundamentally network-driven. This divide is exposing stark differences among operators. Those that have invested in programmable infrastructure, modernized OSS and BSS platforms, and embraced automation are far better positioned to support AI workloads. Others, still reliant on legacy architectures, face mounting pressure as AI places new demands on performance, determinism, and scalability.
Network-as-a-Service (NaaS) is emerging as a critical enabler in this transition, particularly in sovereign markets such as the Gulf. While NaaS itself does not improve raw network performance, it fundamentally changes how enterprises consume connectivity. Through NaaS platforms, customers can define where connectivity is needed, at what performance level, and on what timeline — and then procure those services dynamically. For AI workloads that require precise control over latency and bandwidth, this transparency and flexibility is becoming essential. However, delivering NaaS at scale introduces new complexity, especially when services extend beyond a single operator’s footprint. Automation and interoperability are no longer optional. Standardized, open APIs are the foundation that allows networks to interconnect, orchestrate services across domains, and support AI-driven consumption models.
This is where adherence to industry-wide standards and certifications play a decisive role. Operators with mature, programmable networks produce higher-quality NaaS offerings. By building on proven standards, service providers gain confidence internally, while enterprises gain assurance around performance, reliability, and service expectations.
Mplify’s ongoing work around standards-based Lifecycle Service Orchestration (LSO) automation APIs and its expanding certification programs, including Carrier Ethernet Certification for Business and Carrier Ethernet Certification for AI, reflect a broader industry shift toward verifiable, automated network supply chains. In the Gulf region, where trust, sovereignty, and performance guarantees are paramount, certification will also serve as a powerful differentiator, providing tangible proof that a network is not just “AI-enabled” in theory, but capable of supporting AI workloads in production environments.
LSO API adoption is already gaining momentum, with a growing ecosystem of operators moving from trials into production. As AI strategies mature across the Middle East, the winners will not be defined solely by compute or models, but by networks that are programmable, interoperable, and provably ready for AI at scale. In this next phase of digital infrastructure, the ability to certify network capabilities may matter just as much as the ability to deploy them.
