Tag: managed

AI Transforming Managed Network Services in the Coming Years In the year 2024, the majority of service providers highlighted in Gartner's Magic Quadrant for global WAN services and Magic Quadrant for managed network services reports have begun utilizing artificial intelligence (AI) in various aspects to enhance enterprise network operations. These include AI for IT operations (AIOps), generative AI (GenAI) as a network assistant, improved service delivery, and AI in secure access service edge (SASE) and network security. AIOps has emerged as a crucial capability in managed networking, with leading service providers like HCLTech, Microland, and NTT Data integrating AIOps and network automation for better service onboarding and customer experience. Additionally, AI and machine learning (ML) are being used to monitor network health, detect anomalies, and automate routine tasks in network operations centers (NOCs). The aim is to transition from reactive troubleshooting to proactive assurance. For instance, if there is intermittent latency spikes on a wide-area network (WAN) link, a machine learning model can identify this pattern as a precursor to link failure and alert engineers or trigger failover to prevent a major outage. One such example is Tata Communications, which has invested in AI-based fault diagnosis with 85% accuracy, while utilizing AI-driven telemetry for proactive network monitoring. Furthermore, many network equipment suppliers now incorporate AI features to assist service providers in network monitoring. GenAI as a Network Assistant Managed network service (MNS) providers are increasingly exploring the application of GenAI in IT operations and network management. The vision is to offer a network AI assistant that can interact with operations teams through a natural language chat interface, troubleshoot issues, document networks, and even implement changes by generating configurations based on intent. For example, HCLTech is focusing on leveraging GenAI integrations with software-defined wide-area networking (SD-WAN) to provide complete automation for lifecycle operations. They are developing a supplier-focused GenAI large language model (LLM) within their service delivery platform (SDP). Enhanced Service Delivery AI is also playing a significant role in enhancing customer-facing aspects of MNS. Service providers are increasingly utilizing AI to enhance support and transparency for clients. This includes AI-powered customer service bots, service portals, and AI-generated reports or insights. Many MNS providers leverage bots, enhanced with AI capabilities, to automate repetitive tasks. Some have extensive bot networks as part of their network automation strategies. AI in SASE and Network Security AI and ML are becoming crucial in the security domain of MNS, with service providers like XTIUM and Microland offering AI-powered enhancements to their network security solutions. These platforms utilize advanced analytics, AI, and GenAI to simplify and strengthen the management of LAN, WAN, and cloud security. For SASE and network security, AI can be utilized for automated anomaly detection, quarantining suspicious devices, or triggering multifactor authentication for abnormal user behavior. Additionally, AI can recommend security policy adjustments based on observed usage, such as suggesting zero-trust rules for applications based on contextual factors. Looking ahead to 2028 and beyond, the integration of AI in MNS is expected to significantly enhance operational efficiency and decision-making, ensuring networks are adaptable to changing demands and traffic patterns through AI-driven automation. Embracing AI in Network Operations By 2028, GenAI is anticipated to become a mature and trusted assistant in network operations, offering robust network AI assistants embedded in MNS workflows. These assistants will interact through natural language interfaces, integrated with monitoring and ticketing systems, capable of handling complex queries, drafting change plans, and summarizing incidents and problems. Furthermore, AI agents are expected to evolve into automated responders, capable of perceiving network incidents, making autonomous decisions, and executing actions without human intervention, enhancing service reliability and efficiency. This article is based on an excerpt from Gartner's AI will transform managed network services in the next three years report, authored by Gartner's senior director analyst Gaspar Valdivia.

Tag: managed

Gartner: How AI will transform managed network services

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