Data center operators have always contended with challenges related to power and connectivity availability when building out their vast infrastructure, where they have traditionally focused on geographic locations with affordable power that may not have great access to reliable connectivity. The era of AI only amplifies the difficulty of this predicament, with AI models consuming massive amounts of energy to complete data-intensive computations, but also requiring reliable, high-capacity connectivity for real-time functionality.
In reality, AI’s power sourcing requirements are of lesser concern to enterprises and carriers because these challenges are focused in data centers, but carriers can implement numerous strategies focused on reliability, reach and other operational facets to assist enterprises looking to leverage these applications. So, where do Internet carriers fit into this puzzle, and what benefits can they offer to their enterprise customers by integrating AI into their own operations?
Enhanced Automation and Efficiency
The technology industry remains abuzz with excitement over the possibilities for improved efficiency with the integration of AI, and for good reason. For Internet carriers specifically, AI presents possibilities for enhancing network automation and overall efficiency. This is a crucial benefit for an industry that has traditionally relied heavily on manual network operations and remediation. When integrated internally into network operations, AI can enable better fault prediction through intelligent algorithms that help carriers leverage their massive data sets to streamline operational processes and improve network reliability.
Improving Network Reliability in an Unreliable World
These network reliability and efficiency benefits are crucial amid increased instances of geopolitical sabotage, accidental fiber damages and weather-related outages that threaten the seamless connectivity crucial for serving enterprises and their customers. When integrated into network operations, AI models can help carriers analyze historical and real-time telemetry data to predict possible equipment issues or fiber degradations before they affect network operations. These models can also empower carriers with improved anomaly detection and fault localization through algorithms that continuously monitor for anomalous patterns in network quality, including packet loss, jitter and latency spikes, ultimately improving mean time to repair.
AI is Nothing Without Trustworthy Data
AI’s benefits for network operations are numerous, including improved incident response through proactive maintenance and automated customer service chatbots. These algorithms can help operators reach greater visibility of network incidents by understanding exactly what has happened and more quickly providing relevant information to the right customers, hopefully before they even realize the incident has occurred. These various benefits all support customer experience optimization, which is many operators’ true differentiator in a competitive industry landscape where most Tier-1 service providers offer similar solutions. However, AI models are only as good as their training data, meaning carriers must leverage high-quality, trustworthy data to unlock AI’s full potential in streamlining network operations and (partially, but not fully) reducing the need for manual network remediation.
Striking a Delicate Balance
While this technology is undoubtedly impressive, the telecommunications industry is now contending with heightened energy-sourcing challenges to support AI’s power-hungry operations. These machine learning algorithms require massive computing power within data centers hosting GPUs and ultra-low latency interconnection between them, necessitating tremendous amounts of energy. Navigating these obstacles is paramount for data center operators in serving enterprise customers who wish to leverage AI’s multifaceted benefits. But what role do carriers play, and how can they help enterprises utilize these emerging applications effectively through high-capacity connectivity?
Carrier-Level Strategies in the Era of AI
Of course, carriers can benefit enterprises most by providing reliable access to (and between) data centers that offer AI services, but this requires an expansive reach and optical networking infrastructure optimized to transfer these massive data volumes. This is an age-old problem that is only getting more difficult, with data center operators building infrastructure based primarily on access to cost-efficient energy with less emphasis on proximity to reliable Tier-1 connectivity. Data center operators can probably find greener, cheaper energy in places like Northern Canada or the most northern parts of the Nordics, but these regions lack access to high-capacity networks. This difficult balance means that an expansive network reach on the carrier side is crucial for extending access to areas with better energy availability where data center operators prefer to build, particularly amid AI’s tremendous power requirements.
Unlocking AI’s Potential Through Careful Network Planning and Operations
Carriers have the chance to reap numerous benefits in the era of AI, which presents various operational benefits and business opportunities for supporting enterprises that also want to leverage these emerging applications to drive value creation. AI holds significant promise in helping Internet carriers operate more self-driving networks, though we are still a long way from completely autonomous networks. However, carriers must enhance their network footprints with an emphasis on reliability, capacity and reach by carefully planning continuous expansions to enable AI’s benefits for enterprises. Through thoughtful network planning and other methods, carriers hold the power to provide foundational connectivity that supports enterprises’ emerging applications, helping their customers unlock AI’s full potential as data centers work to solve AI’s energy-sourcing challenges.
