Actionable Benefits
- Identify where private 5G, Wi-Fi 6E/7, fixed line, industrial Ethernet, network slicing, 5G Fixed Wireless Access (FWA), and Low Earth Orbit (LEO) satellites fit within enterprise Artificial Intelligence (AI) connectivity architectures.
- Benchmark enterprise AI connectivity strategies against Information Technology (IT) leadership priorities for hybrid compute, on-premises workload retention, modular modernization, governance, and Return on Investment (ROI) frameworks.
- Compare vendor positioning across networking and security, private cellular, industrial wireless, edge infrastructure, interconnection, compute, and AI infrastructure ecosystems.
Research Highlights
- Insights from senior enterprise decision makers, including Chief Information Officers (CIOs), Chief Technology Officers (CTOs), heads of IT infrastructure, and AI strategy leaders, on AI adoption, Edge AI, and Physical AI workload placement, cloud and on-premises investment, security, compliance, governance, ROI, and vendor selection.
- Assessment of workload placement across device edge, gateway edge, on-premises/private cloud, telco edge, and hyperscale cloud, including latency ranges, hardware examples, workload types, and data movement patterns.
- Evaluation of a four-gate workload placement framework covering data sovereignty and compliance, resiliency and autonomy, latency sensitivity, bandwidth cost and availability, and cloud-on-merit defaults.
Critical Questions Answered
- How will enterprise AI shift infrastructure strategy from cloud-first deployment to deliberate workload placement across device, gateway, on-premises, telco edge, and hyperscale cloud environments?
- Which AI workloads should remain at the device edge, gateway edge, on-premises/private cloud, telco edge, or hyperscale cloud based on latency, data volume, sovereignty, and cost constraints?
- How should enterprises evaluate the trade-offs between private cellular, Wi-Fi 6E/7, network slicing, 5G FWA, fixed line, industrial Ethernet, and LEO satellite for AI and edge compute deployments?
- How are security, networking, compute, Operational Technology (OT), Wi-Fi, and private 5G boundaries converging as operational AI moves into distributed enterprise environments?
Who Should Read This?
- Private 5G, industrial wireless, and enterprise networking providers developing AI-ready connectivity offerings for operational environments such as manufacturing, logistics, energy, mining, transportation, and public safety.
- Compute, accelerator, server, and AI infrastructure vendors aligning product roadmaps with enterprise demand for workload-right placement across device edge, gateway edge, on-premises/private cloud, telco edge, and hyperscale cloud.
- Product, strategy, and business development leaders at enterprise connectivity providers building recurring, Service-Level Agreement (SLA)-backed operated service models that combine Radio Frequency (RF), Internet Protocol (IP) networking, security, OT integration, and cloud economics.
Companies Mentioned
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