The network has become a critical foundation for AI success
For the third consecutive year, NTT DATA has been named a Leader in Gartner's Magic Quadrant for Managed Network Services — a recognition that speaks to something larger than corporate achievement. As artificial intelligence reshapes what enterprises demand from their infrastructure, the network has quietly become the nervous system of modern business, and the companies that understand this shift earliest will define the next era of digital operations. NTT DATA's sustained positioning reflects an industry in transition, where the old boundaries between network, cloud, and security are dissolving into something more unified and, increasingly, more autonomous.
- Enterprises scaling AI workloads are discovering that legacy networks were never designed for the latency, throughput, and security demands that intelligent systems require — creating urgent pressure to rethink infrastructure from the ground up.
- The fragmentation of managing campus networks, SD-WAN, IoT, and cloud security as separate systems is costing organizations time and resilience, and the industry is responding with calls for consolidation.
- NTT DATA is positioning its edge-to-cloud, cloud-native platform as the answer — integrating automation and orchestration across network, cloud, and security domains simultaneously to reduce operational complexity.
- The company's next move is agentic AI: autonomous systems that shift network management from reactive incident response to continuous, self-optimizing intelligence before users ever notice a problem.
- A third consecutive Gartner Leader designation, backed by $30 billion in revenue and operations in over 70 countries, signals that this strategy is producing measurable outcomes — not just a compelling pitch.
NTT DATA has earned a Leader designation in the 2026 Gartner Magic Quadrant for Managed Network Services for the third year running — a milestone the Tokyo-based firm, which serves three-quarters of the Fortune Global 100, treats as confirmation that its network strategy is aligned with where enterprise technology is heading.
The company's managed services cover the full infrastructure stack: campus networks, SD-WAN, internet connectivity, network security, and IoT. What sets its approach apart is the integration of these services across edge and cloud environments through a cloud-native platform built to reduce the fragmentation enterprises typically face when managing these systems in isolation. Automation and orchestration run across network, cloud, and security domains simultaneously.
Rob Mello, who leads NTT DATA's network solutions division, has argued that as AI initiatives scale inside organizations, the network stops being background plumbing and becomes a business-critical asset. AI workloads carry different latency profiles, throughput demands, and security requirements than traditional enterprise traffic — and NTT DATA's pitch is that it has engineered its services around that distinction.
Looking forward, the company is investing in agentic AI: autonomous systems capable of making decisions within defined parameters to continuously optimize network performance. The ambition is to move beyond the reactive, monitor-and-respond model that defined managed services for the past decade, toward networks that anticipate degradation and self-correct before users are affected.
The broader context matters here. Enterprises are consolidating vendors and seeking partners fluent in both traditional infrastructure and modern cloud and AI architectures. NTT DATA's scale gives it the capacity to invest in these capabilities at a level most competitors cannot match — and three consecutive Gartner Leader placements suggest that investment is translating into outcomes clients can actually measure.
NTT DATA has secured a position as a Leader in the 2026 Gartner Magic Quadrant for Managed Network Services, marking the third time in as many years the company has earned this designation. The Tokyo-based technology services firm, which serves three-quarters of the Fortune Global 100, views the recognition as validation of its strategy to build networks that can handle the demands of enterprise AI adoption.
The company's managed network services span the full infrastructure stack: campus networks, SD-WAN deployments, internet connectivity, network security, and IoT services. What distinguishes NTT DATA's approach, according to the company, is the integration of these services across edge and cloud environments, delivered through a cloud-native platform designed to reduce operational complexity. The architecture emphasizes automation and orchestration across network, cloud, and security domains simultaneously—a consolidation that aims to cut through the fragmentation enterprises typically face when managing these systems separately.
Rob Mello, who leads NTT DATA's network solutions and connectivity division, framed the Gartner recognition as evidence that the company's thesis about networks and AI is resonating with clients. As organizations scale their artificial intelligence initiatives, he argued, the network itself has become a business-critical asset rather than mere plumbing. The implication is straightforward: a network designed for AI workloads behaves differently from one built for traditional enterprise traffic. It must handle different latency profiles, throughput demands, and security postures. NTT DATA's pitch is that it understands this distinction and has engineered its services accordingly.
Looking ahead, the company is investing in what it calls agentic AI—autonomous systems that can make decisions and take actions within defined parameters—to further automate network operations. The goal is to move from reactive troubleshooting to proactive intelligence, where the network itself anticipates problems and adjusts before users experience degradation. This represents a shift from the managed services model of the past decade, where vendors monitored systems and responded to incidents, toward a model where AI agents continuously optimize performance.
NTT DATA's position in the Gartner assessment reflects broader industry trends. Enterprises are consolidating vendors and seeking integrated solutions rather than point products. They want partners who can speak fluently about both traditional network infrastructure and modern cloud and AI architectures. The company's $30 billion revenue base and presence in over 70 countries give it the scale to invest in these capabilities at a level smaller competitors cannot match. The third consecutive Leader designation suggests that investment is translating into tangible client outcomes—the metric Gartner analysts use to distinguish Leaders from other quadrant positions.
Citas Notables
As organizations scale their AI ambitions, the network has become a critical foundation for success. We're focused on helping clients build secure, high-performing networks that support real business outcomes.— Rob Mello, Head of Network Solutions and Connectivity, NTT DATA
La Conversación del Hearth Otra perspectiva de la historia
What does it actually mean for a network to be built for AI? That phrase gets used a lot, but what changes?
The traffic patterns are fundamentally different. Traditional networks were optimized for human-initiated requests—someone opens a browser, clicks a link, waits for a response. AI workloads generate enormous volumes of data movement between compute nodes, often with very tight latency requirements. A network designed for that has to think about bandwidth differently, about where data lives, about security at scale.
So this isn't just marketing language about AI?
No. It's a real architectural problem. If you're running large language models or training datasets across distributed infrastructure, your network becomes a bottleneck if it wasn't designed for that. NTT DATA is saying they've engineered their services with that reality in mind.
Why does Gartner naming them a Leader matter? Isn't that just analyst opinion?
It matters because enterprises use these assessments to shortlist vendors. If you're a Fortune 500 company evaluating managed network services, you're probably starting with the Leaders quadrant. Three consecutive years means it's not a one-time achievement—it suggests consistency.
The press release mentions agentic AI. What's the difference between that and regular automation?
Regular automation follows rules you've written: if this happens, do that. Agentic AI can reason about situations, make trade-offs, and act autonomously within guardrails. In a network context, that means the system could decide to reroute traffic, adjust security policies, or allocate resources without waiting for a human decision.
That sounds like it could go wrong.
It could. Which is why the guardrails matter. But the alternative—having humans manually manage networks at the scale enterprises operate now—doesn't scale either. The bet is that autonomous systems, properly constrained, will be more reliable than human-driven processes.