Gartner: How AI Will Transform Managed Network Services

Why It Matters

The AI infusion accelerates operational efficiency and reliability, giving providers a competitive edge while reducing outage costs for enterprises. As networks become more autonomous, businesses can expect faster issue resolution and stronger security postures.

Key Takeaways

• AIOps adopted by providers to shift from reactive to proactive management.
• GenAI assistants built for NOC workflows, aiming full deployment by 2028.
• AI-driven SASE solutions use ML to automate threat detection and policy optimization.
• Provider‑specific fine‑tuned models become differentiators in network fault diagnosis.
• Agentic AI expected to handle Tier 0 remediation, reducing human intervention.

Pulse Analysis

Artificial intelligence is rapidly becoming the backbone of managed network services (MNS). Early adopters such as HCLTech, Microland, and NTT Data have layered AIOps onto legacy NOC processes, enabling real‑time anomaly detection, automated ticket creation, and predictive maintenance. This shift from manual troubleshooting to proactive assurance reduces mean‑time‑to‑repair and frees engineers to focus on higher‑value projects, while enterprises benefit from fewer service interruptions and lower operational spend.

The next wave centers on generative AI and its role as a network assistant. Providers are training large language models on proprietary telemetry and configuration data, allowing operators to query network health, generate change scripts, or draft incident reports in natural language. In the security arena, AI‑enhanced SASE platforms from Versa and Cato are leveraging machine learning to continuously refine threat models and recommend zero‑trust policies, delivering more granular protection without manual rule‑crafting. These capabilities differentiate vendors that invest in fine‑tuned models, turning AI into a marketable service layer.

Looking ahead to 2028, Gartner predicts mature GenAI assistants embedded in every NOC and the emergence of agentic AI capable of Tier 0 remediation. Autonomous agents will perceive incidents, evaluate policy constraints, and execute corrective actions—such as rerouting traffic or applying patches—without human approval unless escalation is required. This evolution promises near‑real‑time self‑healing networks, tighter security postures, and a new competitive frontier where proprietary AI models become strategic intellectual property for service providers.