Dell’s Six Imperatives Outline the Pragmatic Roadmap from Open RAN Foundations to Scalable AI-Native Telecom

Executive Summary

On July 23, 2026, Dell Technologies published a detailed follow-up to its Telco AI Readiness Index 2026 and the companion Open Network Index (ONI) 2026. The report distills operator research into six concrete imperatives that move the industry beyond pilot-stage enthusiasm toward disciplined, monetizable AI-native operations. Critically, the analysis positions Service Management and Orchestration (SMO) and RAN Intelligent Controller (RIC) layers as the near-term, lowest-disruption entry point for AI value in the Radio Access Network—precisely where Open RAN architectures have already begun to demonstrate automation gains.

For operators and vendors navigating the shift from disaggregated, cloud-native Open RAN to GPU-accelerated, AI-native platforms, Dell’s framework offers a realistic sequencing: prioritize data strategy and organizational readiness first, leverage existing RIC/SMO investments for quick wins in energy optimization and closed-loop control, then expand into metro-edge AI services. The message is clear: AI-RAN is not a forklift replacement for Open RAN but its logical, software-speed evolution.

Imperative 1: Organizational Transformation and Early-Win Business Cases

The Readiness Index reveals a stark divide—only a small cohort of operators qualify as “AI visionaries,” while roughly half remain laggards. The gap is execution, not ambition. Dell recommends Centers of Excellence, cross-functional operating models, and rapid deployment of high-impact use cases such as network assurance, security, energy management, and service operations.

This mirrors the Open RAN experience: multi-vendor disaggregation has progressed more slowly than projected, yet the automation layers (SMO and RIC) have delivered measurable operational improvements. Operators that treat AI as a series of isolated experiments will stall; those that institutionalize early wins—documenting reusable patterns in energy savings or predictive maintenance—will build the internal confidence and skill base required for deeper AI-RAN adoption.

Imperative 2: Data Strategy as First-Order Priority

Data readiness remains the weakest link across the industry. Legacy analytics programs have left operators with siloed, non-model-ready telemetry that cannot support real-time AIOps or agentic systems. Dell emphasizes a purpose-built telecom data strategy encompassing governance, common data models, telemetry normalization, and real-time processing pipelines.

In an Open RAN context, this directly augments the standardized interfaces (O1, O2, E2) that already enable richer observability than traditional monolithic RANs. Without this foundation, even sophisticated RIC xApps/rApps or future E3/D-app extensions will underperform. Dell positions its AI Data Platform and enterprise storage solutions as enablers for turning network telemetry into trusted, reusable AI fuel.

Imperative 3: Broader Partnership Ecosystems Beyond Technology

Technology partnerships alone are insufficient. The ONI shows operators engaging a wider array of partners as they pursue open architectures. AI-native transformation demands coordinated efforts across infrastructure, operating models, data services, and vertical go-to-market motions.

This aligns with Open RAN’s multi-vendor ethos. Dell’s neutral, open-ecosystem stance—validated across NEP software stacks and silicon partners—positions it to bridge the cloud-native modernization already underway with the next wave of AI-native workloads. Operators gain a single partner that can integrate disaggregated RAN elements with GPU-accelerated edge nodes without vendor lock-in.

Imperative 4: Monetization via GPUaaS, Sovereign AI, and Edge AI Services

AI transformation must deliver top-line growth, not merely OPEX reduction. The report highlights rising interest in GPU-as-a-Service, AI-as-a-Service, sovereign AI offerings for regulated industries, and edge AI services that bundle connectivity, compute, security, and low-latency inference.

Open RAN’s disaggregation and virtualization already create the architectural preconditions for these models. The metro edge—where distributed cloud infrastructure, local data processing, and enterprise demand converge—emerges as the strategic bridge. With 68% of operators already running at least one edge use case and 56% expecting edge AI support within two years, the ONI data underscores that AI monetization will happen first at the edge rather than in the core.

Imperative 5: SMO/RIC-Led AI for Near-Term RAN Value

Here Dell’s analysis is most directly relevant to the Open RAN community. While multi-vendor Open RAN has advanced more slowly than anticipated, operators continue to see clear value in SMO/RIC automation for closed-loop optimization, energy management, and predictive maintenance. These layers represent the lowest-disruption on-ramp to AI in the RAN.

As confidence grows, investment can extend toward the baseband edge using GPUs or custom silicon—precisely the trajectory of emerging AI-RAN platforms. Dell’s purpose-built telecom and edge servers, optimized for space, power, and validated with leading NEP stacks, are designed to support this convergence of RAN and AI workloads without requiring wholesale hardware replacement.

Imperative 6: Metro Edge as the Near-Term Growth Engine

The metro edge is not a peripheral initiative but a core strategic priority. It links the cloud-native infrastructure investments operators have already made with the AI-driven services and distributed inference capabilities they now seek to monetize. Enterprise and B2B use cases dominate edge strategies, and AI-enabled applications are becoming primary investment drivers.

For Open RAN operators, this means prioritizing metro-edge nodes that can host both RIC applications and emerging AI workloads. The result is a unified platform supporting not only network optimization but also vertical solutions in manufacturing, public sector, healthcare, and smart environments—delivering the sovereignty, latency, and security enterprises demand.

Strategic Implications for Open RAN Operators and Vendors

Dell’s six imperatives collectively describe a single transformation arc: continue modernizing toward open, cloud-native architectures while accelerating the shift to AI-native operating models. Open RAN is not supplanted; it is the essential foundation. The RIC/SMO layer provides immediate AI value, data strategy unlocks scalability, organizational readiness ensures execution, and edge monetization delivers the business case.

Vendors that align their roadmaps with this sequencing—offering validated, power-efficient infrastructure for both traditional RIC workloads and future GPU-accelerated AI-RAN functions—will capture disproportionate share. Operators that execute the imperatives in order will move from pilots to production at software speed, turning the RAN from cost center into AI platform.

Risks and Realistic Timelines

Execution gaps remain material. Data transformation is multi-year work; organizational change is even harder. GPU power and thermal characteristics in edge environments require careful validation. Yet the research indicates operators are already concentrating spend where disruption is lowest and returns clearest—exactly the disciplined approach the market needs.

Conclusion

Dell’s July 2026 analysis does not promise overnight revolution. Instead, it delivers a pragmatic, research-backed playbook that respects the realities of Open RAN adoption while charting the clearest path to AI-native scale. Operators and their ecosystem partners who internalize these six imperatives will be best positioned to capture both operational efficiencies and new revenue streams in the AI era.

Sources

• https://www.dell.com/en-us/blog/six-imperatives-to-accelerate-the-ai-native-telecom/
• https://www.networkworld.com/article/4200815/why-enterprises-should-care-about-nokias-ai-ran-platform.html (contextual reference for AI-RAN platform evolution)
• https://www.fierce-network.com/fiercenetworkcom/ai-drive-ai-ran-rewiring-radio-network-ai-era (contextual reference for broader AI-RAN discussion)