Keith Lee explores how HCI, virtualisation and resilient data centre architectures can help GCC enterprises balance AI ambitions with cost, security and operational complexity
AI adoption across the GCC is accelerating, but building the right infrastructure foundation remains a critical challenge for enterprises navigating rising costs, operational complexity and evolving workloads. From GPU capacity and hyperconverged infrastructure to virtualisation and disaster recovery, organisations are reassessing how their data centres can support AI while remaining secure, scalable and cost-efficient.
In an interview with TahawulTech, Keith Lee, Cloud Business Director at Sangfor Technologies, discusses the infrastructure priorities shaping AI readiness and explains how simplified, integrated architectures can help enterprises modernise operations, strengthen resilience and prepare for emerging workloads.
Interview Excerpts
What infrastructure requirements do organisations most often underestimate when preparing for AI adoption?
One of the most underestimated aspects of AI adoption is the infrastructure needed to run workloads reliably, securely and cost-effectively. Organisations often focus on applications and models while overlooking demands on GPUs, storage, networking, data protection and operational expertise.
“GPU capacity requires careful allocation, monitoring and optimisation to avoid high costs and underutilisation.”
AI also needs scalable, high-performance storage and networks capable of moving large volumes of data efficiently. Skills remain another challenge, requiring expertise across infrastructure, security and operations. Sangfor addresses these requirements through an integrated platform combining compute, storage, networking, security, virtualisation and management for AI deployment.
How are CIOs across the GCC balancing AI ambitions against rising infrastructure costs and operational complexity?
Across the GCC, AI has become a strategic priority, but rising infrastructure costs and operational complexity remain key challenges. CIOs are increasingly prioritising workloads that deliver measurable value while avoiding overinvestment in hardware. Growing costs for servers, GPUs, storage and software, alongside complex multi-vendor environments, are putting additional pressure on IT budgets. Sangfor addresses these challenges through hyperconverged infrastructure and software-defined architecture, integrating compute, storage, networking, virtualisation and security into a unified platform. This approach helps organisations reduce complexity, optimise resources and scale according to demand, enabling CIOs to build AI infrastructure that is cost-effective, flexible, secure and sustainable.
Why are enterprises re-evaluating their virtualisation strategies and exploring alternatives to traditional platforms?
Enterprises are re-evaluating virtualisation as it evolves from server consolidation into a foundation for private and hybrid cloud, AI, disaster recovery and business-critical applications. Rising licensing costs, vendor lock-in and operational complexity are driving CIOs to seek greater flexibility and control. Sangfor offers an integrated alternative combining virtualisation, hyperconverged infrastructure, software-defined storage, networking, security, backup and disaster recovery. This enables organisations to simplify data centre operations, reduce dependence on complex multi-vendor environments and modernise infrastructure. The objective goes beyond replacing a hypervisor, helping enterprises build an agile, secure, cost-efficient and future-ready platform supporting traditional applications and emerging AI workloads.
What role is hyperconverged infrastructure playing in building AI-ready environments?
Hyperconverged infrastructure (HCI) plays a key role in building AI-ready environments by bringing compute, storage, networking, GPU resources, security and management into a unified architecture. Traditional infrastructure can involve multiple systems and management platforms, increasing deployment time and operational complexity. HCI simplifies this foundation, enabling IT teams to deploy resources faster, scale efficiently and manage workloads more easily. For AI, it can support GPU-enabled servers, high-performance storage and flexible compute requirements while allowing organisations to expand gradually as use cases mature.
“Sangfor HCI provides a software-defined platform designed to deliver a scalable, secure and cost-effective foundation for AI workloads.”
How can organisations strengthen business continuity and disaster recovery through modern multi-data-centre architectures?
Business continuity and disaster recovery are now board-level priorities amid growing cyberattacks, ransomware, outages and regulatory requirements. Multi-data-centre architectures reduce reliance on a single site, enabling active-passive or active-active environments based on business needs. Sangfor HCI provides high availability within data centres, automatically restarting virtual machines following server failures. Across sites, Sangfor Disaster Recovery Management supports virtual machine replication and orchestrated recovery, helping organisations meet RTO and RPO objectives. By integrating infrastructure, virtualisation, backup and disaster recovery, Sangfor simplifies visibility, automation, testing and recovery, enabling GCC organisations to strengthen resilience, protect critical services and maintain compliance as digital transformation and AI adoption accelerate.
Source: Tahawul Tech