Prakash Mana, CEO of Cloudbrink, on Why Network is the Key to Thriving in the AI Era

Cloudbrink's CEO, Prakash Mana, has shed light upon the critical role of networking infrastructure amidst the constantly evolving AI landscape. Artificial intelligence is continuing to drive transformation. Organizations that modernize their networking and security frameworks will be best positioned to leverage AI opportunities.

According to Prakash Mana, the increasing prevalence of AI in professional environments has sparked a wave of claims from networking vendors claiming AI-ready or AI-enabled solutions. He, however, cautions that the term "AI networking" lacks clarity and is ambiguous. "There are three fundamental ways AI is reshaping networking: increasing demands on network performance and capacity, driving AI-powered enhancements within networking platforms, and exposing the limitations of legacy architectures," Mana explained.

He emphasized that the first trend, which is AI’s growing demand on networks, will inevitably fuel the second. In this second trend, AI is capitalized to optimize performance, security, and automation. Without AI-driven enhancements, networks will struggle to cope with the capacity, security, and performance challenges that come with AI’s rapid adoption. It was pointed out that traditional network architectures were already strained in an environment where users and applications are highly distributed. The rise of AI will only accelerate these pressures.

Some industry shifts that intersect with AI’s impact on networking are as follows:

  • Cloud and Edge Migration: The mass transition of enterprise applications from traditional data centers to cloud environments has created varying proximities between applications and users.

  • As-a-Service Models: Networking and security are now being delivered through flexible, hardware-free models, mirroring the transformation seen in compute and storage.

  • Hybrid Work Evolution: With applications, users, and data dispersed globally, networking has shifted from centralized models (MPLS) to distributed frameworks like SD-WAN and SASE.

  • Security Integration: The traditional approach of routing traffic through data centers or distant cloud regions (known as cloud hairpinning) is no longer viable. Security measures must now be embedded at the network edge to minimize performance degradation.

  • Network and Security Convergence: Managing networking and security as separate entities increases complexity and risk. Organizations must integrate policies to simplify operations and enhance protection.

The important networking requirements in an AI-driven world can be distilled into three priorities: speed, security, and simplification. These factors, already critical, will become non-negotiable as AI adoption surges in 2025.

The impact of AI on network capacity and performance is a growing concern. "Generative AI will not only consume vast amounts of data but also generate even more. With network capacity doubling every two years and fiber optics reaching physical limits, AI-related traffic could significantly strain every segment of the network," Mana warned. He added that organizations must prepare for an explosion of data traffic requiring faster, more reliable, and more scalable network services.

Beyond sheer capacity, AI-driven applications will stress network performance. Moving massive volumes of dynamically generated content in real-time is already challenging, especially at the network edge. For remote users on consumer-grade broadband, Wi-Fi, or mobile networks, application performance issues will intensify unless latency and packet loss are addressed. Without proper solutions, AI-driven workloads could render some connections unusable.

AI is seen as both the cause of and the solution to these challenges. It can optimize path selection, enhance security, and recover lost packets before they impact user experience. For example, AI can dynamically select the nearest available edge to minimize latency and improve performance, taking into account time-of-day traffic patterns. It must be noted that AI-driven networks can offer better security. This is owing to the fact that they avoid static points of presence that are vulnerable to attacks.

Security remains a concern as AI expands the attack surface for cyber threats. AI makes it easier to launch sophisticated attacks while also enabling new types of cyber risks. Organizations must modernize their infrastructure to stay ahead of these threats. Upgrading networks won’t directly solve all AI-related security challenges, failing to do so will exacerbate them.

Prakash Mana concluded that enterprises investing in AI-ready networking and security frameworks will gain a competitive advantage. "Those who act quickly to modernize their infrastructure will seize AI-driven opportunities, while those lagging behind will struggle under the weight of AI’s demands. The race is on," he stated.

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