How AI-Driven Networks Are Transforming Enterprise Connectivity

The rise of artificial intelligence (AI) is revolutionizing enterprise networks, compelling businesses to rethink their approach to connectivity. Legacy systems, such as Multi-Protocol Label Switching (MPLS) networks, are slowly being replaced by internet-first alternatives. These new network designs are built to address the evolving demands imposed by AI technologies and cloud computing. The transition towards these hybrid models not only enhances cost efficiency but also delivers better bandwidth performance, particularly in global markets facing constant technological evolution.

Understanding the Internet-First Network Model

One of the defining characteristics of an internet-first network is the shift away from heavy MPLS reliance. Companies transitioning to this model prioritize Direct Internet Access (DIA) and business broadband for enhanced underlay solutions. This approach leverages Software-Defined Wide Area Networking (SD-WAN) technologies to optimize network costs while increasing bandwidth capabilities. Secure Access Service Edge (SASE) platforms further boost network security and access management, making these systems resilient and AI-ready.

The most significant advantage of internet-first networks is their flexibility. Enterprises can source the best-in-region or best-of-breed providers for their connectivity needs. This customization ensures top-tier performance for each business location while avoiding the traditionally high costs associated with MPLS systems. As Network as a Service (NaaS) solutions and on-demand sourcing grow in popularity, embracing internet-first models is quickly becoming a necessity, not a choice.

Analyzing the Cost and Performance Impact

Cost analysis highlights the immense potential of internet-first WAN models. Data shows that transitioning to this system allows enterprises to double their bandwidth while maintaining their current budgets. Businesses in highly reliable regions with Fiber to the x (FTTx) infrastructure experience even greater cost efficiency, making broadband an attractive option for secondary connections. However, many organizations prioritize having at least one DIA port for each site, ensuring performance consistency and uptime reliability, particularly in regions with less dependable internet services.

Figures from TeleGeography’s WAN Cost Benchmark reveal intriguing insights. The average bandwidth per site significantly increases under the internet-first model, offering tangible performance improvements. Enterprises gain the ability to service AI-driven applications and cloud services seamlessly, creating more productive and efficient networks. Additionally, the total cost of ownership (TCO) for internet-first networks demonstrates long-term savings compared to legacy MPLS setups.

The Path to AI-Ready Enterprise Networks

As enterprises transition into AI-driven environments, ensuring a robust, scalable, and cost-effective network structure is critical. Many organizations use tools such as the TeleGeography WAN Cost Benchmark platform to evaluate their current setups and explore cost-efficient enhancements. By adopting internet-first strategies, companies eliminate the need to compromise between budget constraints and network performance. Instead, they can invest in AI-optimized networks capable of handling future demands.

The shift to an internet-first architecture presents a clear path forward for global enterprises. Embracing technologies like SD-WAN and SASE can foster greater cloud integration, operational efficiencies, and business growth. As businesses brace for the AI revolution, reliable connectivity underpinned by innovative network models will remain the backbone of their success.