How AI is Reshaping Enterprise Networks: Cost and Strategy Insights
How AI is Reshaping Enterprise Networks: Cost and Strategy Insights
Artificial intelligence (AI) is revolutionizing enterprise networks and driving significant changes in IT infrastructure. As businesses increasingly adopt AI for cloud computing, data analytics, and automation, they are also faced with the challenge of optimizing their networks to handle bandwidth-intensive tasks. The transition from legacy MPLS networks to hybrid or internet-first alternatives has become a critical move for enterprises aiming to future-proof their network systems. Understanding the total cost of ownership (TCO) in the context of different WAN configurations is key to navigating these changes effectively.
The Case for SD-WAN in the AI Era
Traditional MPLS networks, which have been a cornerstone for many multinational enterprises, are struggling to meet the demands of an AI-driven environment. SD-WAN-enabled hybrid networks have emerged as a compelling alternative. Initially promoted as a cost-saving solution, SD-WAN has evolved to offer much more. Enterprises now seek right-sized networks that provide greater resilience, app-specific policies, superior cloud utilization, and the bandwidth necessary to meet AI requirements. For companies just beginning their AI journey, a conservative tiered hybrid WAN is an excellent starting point. This strategy allows for a gradual introduction of internet-first solutions while maintaining a balanced cost-per-bit ratio and seamless operations for proprietary applications or on-premises data centers.
Exploring Tiered Network Strategies
A tiered network strategy involves segmenting network infrastructure into different site categories to better align with varying needs. For conservative enterprises, this approach enables the implementation of SD-WAN and local internet breakout options without fully stepping away from MPLS. This ensures data security, compliance, and resiliency while accommodating moderate bandwidth increases. On the other hand, forward-thinking enterprises already experiencing bandwidth bottlenecks from AI workloads may opt for a Tiered Hybrid model. These networks integrate broadband and DIA services alongside MPLS at key sites, providing cost savings while addressing AI’s extensive bandwidth demands.
Carriers offering Direct Internet Access (DIA) at competitive port-only prices have further incentivized this shift. Urban areas with robust network competition allow enterprises to eliminate additional local access fees, making DIA an appealing alternative for high-bandwidth applications. This budget-conscious decision often enables organizations to unlock the full potential of AI and cloud solutions without significant cost increases.
The Cost Implications of Hybrid Networks
Whether adopting a conservative or aggressive tiered strategy, hybrid networks consistently outperform MPLS on cost-effectiveness and flexibility fronts. DIA and broadband options provide enterprises the agility to scale bandwidth as needed, an indispensable feature for businesses navigating the increasing network strain of AI capabilities. TCO comparisons across Dual MPLS, Conservative Tiered Hybrid, and Tiered Hybrid WAN configurations illustrate that hybrid approaches deliver solid resilience, application performance, and better ROI.
As enterprises move toward integrating AI, it’s crucial to evaluate WAN configurations that align with their bandwidth, product choice, and geographic needs. While cost efficiency remains an important factor, staying ahead requires a focus on scalability and reliability in network performance. These strategic decisions will enable organizations to meet AI-driven demands while unlocking innovation opportunities in a dynamic IT landscape.
