Gulf Business Machines (GBM), a leading end-to-end digital solutions provider, has launched the UAE AI Lab, the first AI Lab in the United Arab Emirates built on the Cisco Secure AI Factory with NVIDIA.
Announced in Dubai on October 7, 2026, the initiative is designed to provide organizations across the Gulf Cooperation Council (GCC) region with secure, full-stack infrastructure capable of supporting the complete AI journey, from initial experimentation through to production.
The launch comes as enterprises across the Gulf increasingly seek to move beyond testing artificial intelligence technologies and begin deploying AI at operational scale, while maintaining strict requirements around security, data governance and digital sovereignty.
From AI Experimentation to Production in Weeks
A key objective of the UAE AI Lab is to significantly reduce the time required for organizations to deploy AI environments. GBM says the infrastructure can help compress deployment timelines from months to weeks, enabling enterprises to accelerate the transition from AI experimentation to production.
The lab allows customers to test secure AI use cases across both on-premises and hybrid environments. This provides organizations with greater flexibility to develop and evaluate AI applications while maintaining control over where their data is stored and processed.
The approach is particularly relevant for organizations operating in sectors where regulatory requirements, data protection and infrastructure security are critical considerations.
Building AI Around GCC Sovereignty Requirements
The UAE AI Lab has been designed to address key requirements associated with sovereign AI across the GCC. These include data residency, regulatory compliance, security and low-latency data processing.
By enabling organizations to test and deploy AI within secure local and hybrid environments, the lab provides an infrastructure foundation designed to support the region’s specific operational and regulatory requirements.
GBM will also offer end-to-end Secure AI Factory architectures, giving organizations access to the infrastructure required for the AI era across the technology stack, from the core data center through to the edge.
Cisco and NVIDIA Power the Secure AI Factory
The lab is built on Cisco’s pre-validated, modular AI infrastructure with NVIDIA. The architecture is designed to bring together high-performance computing and networking while incorporating security across every layer of the AI environment.
This security approach extends across models, agents, workloads and data paths, creating an integrated infrastructure framework for enterprise AI deployments.
The platform also incorporates NVIDIA AI Enterprise, providing the software foundation required to support demanding enterprise AI workloads alongside the underlying accelerated computing infrastructure.
Real-Time Monitoring and Hardware-Level Security
Security is integrated into the architecture from the beginning rather than being treated as an additional layer after deployment.
The platform provides continuous, real-time monitoring of AI workloads and agent activities, while security policies can be enforced in depth at the hardware level.
This integrated approach is intended to give organizations greater visibility and control over AI environments as they scale their deployments and introduce increasingly sophisticated AI applications.
GBM Focuses on the Shift Toward Production-Grade AI
Pieter Bil, CEO at GBM, said regional enterprises are entering a critical stage as they transition from AI experimentation to full-scale operational deployment.
According to Bil, organizations face the challenge of balancing the need for rapid innovation with strict data governance requirements. GBM’s approach seeks to address that challenge by transforming advanced global technology frameworks into secure, locally managed platforms designed around the requirements of the GCC.
The UAE AI Lab therefore represents a practical environment where enterprises can explore AI technologies while addressing the governance and security considerations associated with production-grade deployments.
Cisco Sees Sovereignty as Key to Gulf AI Growth
Cassie Roach, VP of Global Partner Sales, AI Infrastructure & Connectivity at Cisco, said the next phase of AI growth in the Gulf will be shaped by organizations capable of turning AI visions into commercial applications quickly and effectively while maintaining sovereign control and resilience.
Roach highlighted the collaboration between Cisco, GBM and NVIDIA as extending beyond infrastructure deployment. The partnership, she said, is intended to help accelerate the Gulf’s ambition to play a leading role in the global AI economy while allowing organizations in the region to pursue that ambition on their own terms.
NVIDIA Highlights the Rise of Agentic AI Infrastructure
Dirk Barfuss, Director EMEA Channel at NVIDIA, pointed to a broader transformation taking place in enterprise AI infrastructure.
According to Barfuss, enterprise AI is increasingly shifting toward inference-optimized and agentic infrastructure designed to support next-generation applications. NVIDIA’s accelerated computing technologies, combined with NVIDIA AI Enterprise software, are designed to deliver the performance and scalability required by these workloads.
With the launch of the UAE AI Lab, GBM now has a dedicated showcase environment through which organizations across the GCC can explore how this infrastructure can be deployed securely and at scale.
A New Platform for Enterprise AI Across the GCC
The launch of the UAE’s first AI Lab creates a dedicated environment for enterprises seeking to evaluate, develop and deploy artificial intelligence while addressing the security, regulatory and sovereignty considerations associated with modern AI infrastructure.
Built on Cisco Secure AI Factory with NVIDIA, the lab brings together high-performance computing, networking, security, monitoring and enterprise AI software within a pre-validated architecture.
For organizations across the GCC, the initiative is positioned as a bridge between AI experimentation and real-world production, helping enterprises shorten deployment timelines while maintaining control over data, infrastructure and security as their AI strategies evolve.
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