How AI Can Help Solve Networking Problems Quickly and Easily

Artificial intelligence (AI) has revolutionized many industries, and networking is no exception. With the increasing complexity of networks, managing them efficiently is becoming more challenging. However, AI can help solve these networking problems by automating processes, predicting issues before they occur, and optimizing network performance.

One of the primary benefits of AI in networking is automation. AI-powered tools can automate mundane and repetitive tasks, such as network configuration, monitoring, and troubleshooting. This not only saves time but also reduces the risk of human error. With AI automation, networks can be managed more efficiently, and IT teams can focus on more critical tasks.

Enterprise networking professionals must pay attention to and be ready for the potential effects of AI traffic on their networks as AI quickly becomes mainstream with the public release of ChatGPT and Microsoft’s $10-billion investment into OpenAI. The implications of this tech could be both positive and negative.

Network teams and networking professionals should remain up-to-date with the latest trends in AI to stay ahead of the curve as this technology increasingly becomes a core feature in mission-critical software. Both groups should take advantage of the variety of training activities, courses, and other resources available to become familiar with deploying and sustaining AI platforms.

The traditional enterprise network has become stranded due to the shift to cloud technology, leaving enterprises powerless to regain control. As per Andrew Coward, GM of Software Defined Networking at IBM, artificial intelligence and automation must be adopted if they are to do so.

Coward says:

“The center of gravity has shifted from the corporate data center to a hybrid multicloud environment, but the network was designed for a world where all traffic still flows to the data center. This means that many of the network elements that dictate traffic flow and policy are now beyond the reach and control of the enterprise’s networking teams.”

Based on recent Enterprise Management Associates (EMA) research, Coward’s observations were supported as it revealed that. Despite being widely adopted (99%), only a few (18%) enterprises have the right tools to monitor public clouds in their multi-cloud strategies. This is according to EMA’s 2022 Network Management Megatrends report, which surveyed 400 IT organizations.

Utilize AI to Monitor Your Network for Security & Efficiency Automatically

Organizations utilizing AI tools must navigate traffic between their cloud-based data centers and enterprise networks to enable the training of said tools, such as those by OpenAI, IBM Watson, or even AWS DeepLens. This stretches organizations’ networks in both obvious and obscure ways.

To ensure that AI is properly trained and remains current, it must transport enormous amounts of data back and forth.

AI stealthily enters the enterprise, hidden in capabilities embedded into other tools. It is less obvious yet nonetheless a prominent feature that AI has gradually been integrated into multiple applications.

With AI incorporated into various tools, from anti-spam engines to video surveillance software and edge devices, problems could arise due to surges in traffic and connectivity issues across WAN routes between those tools and enterprise data centers.

AI technology is aiding resource-constrained teams in dealing with the complexity of multi-cloud and distributed networks. Specifically, its traffic management and monitoring tools can prove to be a boon by enabling them to cope effectively. On the brighter side, AI-powered tools are thus having a positive impact on these already fragile networks.

AI has become increasingly important for businesses related to network services in today’s digital world. AI is integral to modern services such as SD-WAN, SASE, and 5G owing to features like intelligent routing, load balancing, and network slicing.

Should enterprise leaders trust AI as it assumes more network functions? This is something that certainly needs to be determined, as artificial intelligence fills roles traditionally done by humans.

Is It Wise To Trust AI For Mission-Critical Networking?

Many of the extravagant claims made by AI vendors are being met with a reservation from experts charged with harnessing this technology to power next-generation networking. Skepticism abounds in light of their ambition.

Broadcom Software uplifted its product-management table by adding Jason Normandin as its NetOps Product Manager.

Jason Normandin says:

“Network operations manage what many perceive to be a complex, fragile environment. So, many teams are fearful of using AI to drive decision-making because of potential network disruptions,”

To win over operational teams, an understanding and access to the logic behind an AI model are paramount. With this understanding, winning people over will prove easier.

Jason Normandin went on to say:

“To ensure buy-in from network operations teams, it is critical to keep human oversight over the AI-enabled devices and systems.”

AI that does not leave users in the dark about its “inner workings,” or “Explainable AI,” can incur the trust of networking professionals.

At UST, a company focused on digital transformation, Dr. Adnan Masood is the Chief AI Architect.

Dr. Adnan Masood says:

“Building trust in AI as a reliable companion starts with understanding its capabilities and limitations and testing it in a controlled environment before deployment.”

AI transforms networking by automating tasks, predicting issues before they occur, optimizing network performance, and enhancing security. The benefits of AI in networking are significant, and it is an exciting time for the networking industry as AI continues to advance and revolutionize how networks are managed.

Source: network world

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