Inside the AI-powered evolution of enterprise network operations [Q&A]

Enterprise networks are on the cusp of a significant transformation in which management functions are shifting from hardware-bound systems defined by manual processes and siloed tools, toward intelligent, adaptive infrastructures powered by AI.

In contrast to the reactive troubleshooting of traditional network management, AI introduces predictive capabilities that enable IT teams to anticipate issues, prevent network downtime, and optimize performance before disruptions happen.

We spoke to Laura Lehman, director of digital experience product management for leading networking and security as a service provider GTT Communications, about her perspective on this network paradigm shift. Drawing from her time working with and hearing from organizations that are making this transition, Laura explains the advantages AI will bring to network management and the critical considerations business and technology leaders must take into account.

BN: How is AI transforming network management, and how have enterprise networks evolved?

LL: Historically, enterprise networks have been hardware-centric, static, and reactive. Each network is astoundingly unique, as are the manual troubleshooting and isolated tools used to manage and secure it. Network security and uptime are often achieved through a combination of in-house, vendor, and aggregator solutions.

AI adoption flips traditional network management on its head by replacing hardware and ad-hoc management tools with software-defined, intelligent, and adaptive infrastructures. Enterprises that make this investment gain access to a host of predictive analytics and automation capabilities, enabling IT teams to transition from traditional reactive approaches to proactive, data-driven decision-making. Instead of waiting for something to fail, AI can help proactively identify patterns, anticipate issues, and recommend configuration changes before disruptions occur.

BN: How does AI enable network management to shift from reactive to adaptive?

LL: Initially, network managers had to be detectives. When an incident or failure was noticed, IT teams had to contact their provider and start troubleshooting to narrow down the possible causes. Network detection and response evolved as a result. Network alerts, when accurate, helped managers and providers pinpoint the incident to be triaged, resulting in much faster, more organized responses. These developments marked significant improvements, but they were still reactive.

Now, with AI, we’re entering the adaptive era, made possible by human-guided, intelligent automation. By analyzing historical and real-time data, AI can predict potential failures, whether it’s a device overheating, a pattern of performance degradation, or even external factors like weather conditions. It can then automatically recommend corrective actions such as rerouting traffic, deploying backups, or recommending upgrades before an outage occurs. These capabilities don’t just prevent network downtime — AI acts as a ‘technical manager’ between technical operations and customer experience, translating complex data into actionable insights for the professional services and managed security teams.

BN: How can AI enable IT teams to prevent network disruptions?

LL: It does so by transforming the way IT teams monitor, manage, and respond to potential issues. AI can analyze both historical and real-time data to forecast emerging problems through predictive analytics, enabling teams to take preventive action before downtime occurs. Automated remediation allows AI to quickly diagnose issues and implement or recommend corrective measures — such as reconfiguring network settings. With AI-driven visibility and control, IT teams can gain a unified view of complex multi-vendor networks, which helps them make faster, data-informed decisions. Proactive recommendations from AI systems provide early warnings and actionable insights to maintain optimal performance. Taken as a whole, these capabilities shift network management from a reactive process to an adaptive, automated model that anticipates and prevents disruptions before they affect business operations.

BN: What are some of the broader benefits that AI brings to networking management?

LL: First and foremost, AI empowers IT teams by giving them greater visibility, efficiency, and control over their networks. As with many AI technologies, it also reduces manual workloads and shortens reporting and analytics cycles. In short, it enables IT teams to accomplish more with less, which gives them the bandwidth to focus on proactive network management.

There is also a tangible financial impact. For industries such as retail, finance, and manufacturing, network downtime directly translates to lost revenue. Thus, AI’s ability to help prevent outages and maintain uptime has a measurable business benefit.

Lastly, there are many security-related benefits. AI can help monitor and analyze large amounts of network traffic in real time, detecting anomalies or behavior patterns that may signal a breach. Furthermore, AI can help analysts investigate such incidents to identify threats, triage automatically, and escalate significant threats to specialists with suggested remediation strategies.

BN: What is the future of network operations as the adoption of AI-enabled tools becomes mainstream?

LL: The future of network operations is shaping up to be smarter, faster, and a lot more user-friendly. Yes, AI will enable networks to become proactive and adaptive, but IT teams won’t lose any of their control. In fact, they’ll gain greater visibility across their entire infrastructure, regardless of how many vendors or systems they use, making it easier to stay in control than ever before. Despite these advancements, the fundamental need for human oversight and dedicated security management to define policies, handle exceptions, and respond to novel threats will remain essential. The focus will also become much more user-centric, with AI tailoring dashboards and insights to fit each person’s role. Whether you’re a network admin or in operations, everyone gets the information that matters most to them. Ultimately, AI will help unify complex network environments, simplify decision-making processes, and create a smoother, more reliable experience for both IT teams and end-users.

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