Hewlett Packard Enterprise has been named a Leader in the IDC MarketScape: Worldwide Network Consulting Services 2026 Vendor Assessment as enterprise network modernization becomes increasingly tied to artificial intelligence, cybersecurity and broader infrastructure strategy.
The recognition comes as organizations face growing pressure to upgrade networks that were not originally designed for today’s distributed applications, AI workloads and increasingly automated IT environments.
HPE is positioning its network consulting business around helping customers connect those infrastructure investments to measurable business outcomes rather than treating modernization as a standalone technology project.
Networks Become Part of the AI Strategy
Enterprise networks have traditionally been viewed as foundational infrastructure, but AI is changing what organizations need from them.
Large AI workloads can place new demands on bandwidth, latency, telemetry and data center fabrics. At the same time, organizations must support distributed users, cloud applications, connected devices and expanding security requirements.
That is pushing network strategy closer to broader discussions around AI infrastructure, cloud architecture and cybersecurity.
HPE said its consulting services cover the network lifecycle from strategy and architecture through deployment, validation, operations and optimization.
HPE Brings AI Into Network Operations
AI is also changing how networks themselves are managed.
HPE has incorporated AI-assisted design, digital twins, configuration validation, generative AI workflows and emerging agentic support capabilities into its networking approach.
The company’s portfolio includes HPE Aruba Networking Central, HPE Mist, HPE Marvis and HPE OpsRamp Software alongside internally developed automation technologies.
The goal is to move network management toward a continuous cycle of assessment and optimization rather than relying primarily on manual troubleshooting and periodic infrastructure upgrades.
Automation can also help organizations improve policy consistency, identify issues faster and reduce configuration errors across increasingly complex environments.
Juniper Expands HPE’s Networking Reach
HPE’s network strategy now also incorporates capabilities from Juniper Networks.
The combined portfolio gives HPE a broader foundation across campus, branch, data center and cloud networking while expanding its AI-native networking and automation capabilities.
HPE said its consulting teams can help customers build environments supporting AI model training and inference, hybrid cloud deployments, private 5G, cybersecurity and modern data center infrastructure.
For AI environments specifically, consulting can extend into areas including high-performance data center fabrics, GPU infrastructure, telemetry, segmentation and workload-aware network designs.
Security Becomes Part of Network Modernization
Network modernization is also increasingly tied to cybersecurity.
As organizations distribute applications, users, devices and data across more environments, the network becomes an important enforcement point for security policies.
HPE’s consulting approach incorporates technologies and strategies including zero trust, SASE, network access control, segmentation and operational technology visibility.
That reflects a broader shift in enterprise infrastructure where networking and security decisions are becoming harder to separate.
The Bottom Line
HPE’s Leader position in the 2026 IDC MarketScape comes at a time when enterprise networking is taking on a larger strategic role.
AI workloads, cloud environments, cybersecurity requirements and distributed operations are forcing organizations to reconsider infrastructure that may have been designed for a much simpler IT environment.
For HPE, the opportunity extends beyond selling networking hardware. Combining consulting, automation, AI-native network management and the expanded Juniper portfolio gives the company a way to participate throughout the modernization lifecycle.
As AI adoption expands, the network may become one of the most important, and sometimes overlooked, pieces of enterprise AI infrastructure.