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How rApps are accelerating the journey to autonomous RAN operations

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The path to higher levels of AN maturity with rApps on SMO platform

rApps are becoming the preferred way to introduce advanced automation, support complex use cases, and orchestrate multi-vendor environments. This shift reflects operators’ broader push toward higher levels of autonomous, intent-driven networks in response to rising costs, complexity, and the demand for high performance and better service quality.

Report

This market research by Analysys Mason shows that rApps are rapidly becoming the foundation for advanced RAN automation and progress toward higher levels of Autonomous Networks. Based on a 2026 global survey of Tier 1 operators, the findings highlight the growing role of SMO hosted rApps, agentic AI, and intent based operations, alongside a clear shift toward SaaS delivery models and public cloud platforms to enable scalable, production grade autonomous RAN deployments.

Reduce operational complexity in end-to-end service orchestration

The SMO plays a central role in reducing the complexity associated with co-ordinating end‑to‑end service orchestration. SMO supports standardized and open interfaces that will allow operators to orchestrate closed-loop automation workflows across multi‑vendor RAN environments and reduce operational overheads linked to fragmented toolchains.

The real value of the SMO platform lies in the consistency it brings in terms of standardized APIs and uniform interpretation of network functions and data models from various systems. This also helps us to simplify and speed up the integration effort. Building applications for autonomous networking operations is extremely complicated, so we will end up deploying an SMO platform from a large networking vendor that can support greater scales and cloud-native capabilities.

- General Manager, Wireless Technologies – wholesale operator, Asia–Pacific

Leveraging advanced AI capabilities to address more complex automation

rApps allow operators to integrate AI capabilities into RAN operations such as self-healing and optimization processes to enable more advanced automation. Operators increasingly view public cloud providers (PCPs) as critical partners who provide advanced AI models (including agentic and intent-based AI), model training and compute resources.

Volume of rApps-based automation deployed today, in 2 years and in 5 years. Source: Analysys Mason

Openness as a core architectural strength for greater innovation

The SMO allows operators to unlock a wider innovation ecosystem and flexibly integrate best-of-breed rApps and third-party AI tools to introduce specialized capabilities and extend automation into new and diverse use cases beyond what a single-vendor stack typically offers.

90% or respondents view Agentic AI as either a “Significant” or an “Absolutely critical” enabler of L4/L5 autonomy and intent-based networking.

The upside of the SaaS delivery models

A striking consensus has emerged regarding delivery models for RAN automation software. The need for dynamic, real-time updates to AI models has made traditional perpetual licensing poorly suited to autonomous network environments. As a result, SaaS is becoming the dominant commercial model for rApps.

Which of the following licensing models do you anticipate will become the primary one for rApp deployment as your organization advances towards higher levels of RAN automation? Source: Analysys Mason
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How rApps are accelerating the journey to autonomous RAN operations: a research report by Analysys Mason


Analysys Mason

 

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Recommendations for operators

Adopt an SMO-centric architecture to enable deployment of a wide range of advanced RAN automation use cases by leveraging an open ecosystem of rApps

As networks progress towards higher levels of automation, the number of rApps required to support advanced use cases will increase. SMO provides a standardized platform for deploying and managing increasing volume and diversity of rApps.

Take an ecosystem-focused approach to openness beyond protocol compliance by selecting platforms that enable functioning third-party marketplaces

Operators are increasingly viewing cloud-based tools and solutions that provide advanced AI capabilities as essential for reaching higher levels of AN. SMO provides support for standardized interfaces not just for RAN hardware and software, but also cloud vendors, cloud platforms and cloud-automation tooling.

Align procurement with SaaS models to ensure automation logic and AI models remain updated against evolving operational demands

Autonomous operations require frequent software updates, including security updates, to guarantee network robustness and resilience and uphold sovereignty requirements. SaaS ensures new policies and features can be updated dynamically and scaled on demand without the delays associated with perpetual licensing, enabling operators to meet stringent performance requirements and SLAs.

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