Artificial intelligence is transforming how AI-driven network operations are managed, monitored, and optimized. Telecommunications providers and enterprise IT teams alike are using AI-driven technologies to reduce downtime, improve network performance, and deliver more resilient services.
As networks grow increasingly complex and data-heavy, traditional manual processes can no longer keep up — automation and AI-powered machine learning are now essential for real-time decision-making and predictive insight.
“Network connectivity is critical to any business,” says Nic Benders, Chief Technical Strategist at New Relic.
Even minor interruptions are an emergency — but AI-driven systems allow teams to move from firefighting to foresight by building that experience and intuition into their tools.
AI is also redefining how network performance is thought about, with the complexity of today’s network operations requiring systems that can understand patterns, learn from them, and adapt faster than human operators ever could.
Across telecom, cloud, and enterprise infrastructure, AI-driven network optimization is changing the way providers handle everything from routing optimization to anomaly detection. The result is not just faster performance, but smarter, more resilient systems capable of self-correction at scale.
Key benefits of AI in networking
Forward Networks’ co-founder, Nikhil Handigol, says AI-driven network optimization holds the promise of transforming networks to be reliable, secure, and delivering peak network performance to applications, while offloading tedious, manual tasks from engineers and allowing them to focus on higher-impact, strategic initiatives.
“When built on a foundation of accurate, detailed, always-current information, AI can move faster than any human, with fewer errors, offering a higher level of confidence than human-driven network optimization efforts,” he says.
He adds that what’s even more exciting is that it can surface insights that would have been buried in a high volume of complex data.
“It’s not just about speed; it’s about enabling operators to see what was previously invisible, understand it, and act with confidence,” Handigol says.
AI in network configuration and management
Comprised of tens of thousands of devices from multiple vendors and cloud providers, the network is the backbone of the company.
“The network is one of the most brittle and complex systems in modern IT,” Handigol explains.
A simple typo can take down customer-facing applications, disrupt operations, or open the door to security breaches.
Benders says networking professionals must have a foundational understanding of how modern AI-powered systems work, what they can do, and what they can’t do.
To build this, network engineers and administrators should be sure they are playing around with AI-driven technologies and building experience on AI-driven technical projects, even if those experiments don’t produce anything tangible.
“Some kind of orchestration is also a must-know,” he adds.
There are now lots of “no code” platforms out there, but in the AI-driven network world, it’s also never a bad time to learn Python.
He calls AI “invaluable” for capacity planning, for example, spotting when traffic is about to surge or when bandwidth is running thin, so adjustments can be made in advance.
“Because so many outages are a result of misconfigurations or bad deployments, predictive tools can flag those high-risk changes before they ripple out across the AI-driven network,” Benders says.
Predictive maintenance and network reliability
Misbah Rehman, Vice President of Product Management and Compliance at Alkira, explains that predictive AI-powered systems are especially valuable in keeping networks aligned with desired outcomes.
“Capacity forecasting lets teams right-size bandwidth or choose alternate paths before congestion undermines deterministic performance,” he says.
Change-risk scoring simulates the blast radius of proposed updates and recommends safer rollout strategies, while predictive verification can also highlight when policy drift threatens segmentation or security before it becomes a business-impacting outage.
In cloud-delivered environments, these AI-driven capabilities extend seamlessly across sites, AI data centers, and users—providing resilience without additional infrastructure to deploy.
“All of this makes the network more resilient by design, because you’re no longer reacting after the fact, you’re preventing the incident in the first place,” Benders says.
Future trends and challenges in AI network optimization
Handigol offers a glimpse into the future of AI-driven network operations, proposing a scenario where an application cannot reach the internet.
An AI-powered agentic operations bot would detect the connectivity issue before it affects users. It would gather details about the host, provide a visual representation of its location and reachability, and perform a full path analysis, including identifying where traffic was denied.
The agent could then test what would happen if a firewall permitted the traffic to pass and continue this testing throughout the path. After completing the analysis, the agent could make the necessary firewall rule changes to securely allow connectivity without human intervention.
“If the idea of an agent making firewall changes feels risky, this is where network digital twin technology provides essential guardrails,” he explains.
By running regular network verifications, it ensures that any automated changes do not introduce unintended connectivity issues or break compliance policies.
“We see agentic operations as the future of AI-driven networks,” Handigol says.
These operations will be able to take predictive action to maintain reliability and compliance by monitoring network performance and reasoning through the outcomes of behavioral changes.
“Instead of simply alerting engineers to potential problems, agents will be able to act directly to preserve performance and security,” he says.
Don't let complexity slow you down—empower yourself or your team with CompTIA AI Essentials and master the core skills to optimize and future-proof your networks.