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In today’s constantly evolving telecommunications landscape, networks must support a wide mix of experiences, services, and environments. The convergence of Open Network Architecture (ONA) and AI is beginning to reshape how 5G and future 6G systems are designed, deployed, and optimized. The Open RAN (i.e., ORAN) architecture provides openness and programmability, and AI raises the level of intelligence that networks can deliver across industrial, enterprise, and public settings. With the RAN Intelligent Controller (i.e., RIC) at the centre, AI driven RIC solutions are becoming essential to how modern networks operate.
Setting the Foundation: RIC Roles, xApps and rApps, and Cyient’s AI Direction
Along with this shift, Cyient is strengthening its focus on VISMON AI inside Open RAN, bringing together our Ericsson Intelligent Automation Platform (EIAP) ecosystem work and a well-defined path toward closed loop automation guided by non-RT RIC policies sent through the A1 interface.
It is also important to clarify that xApps and rApps are not inherently AI. They are control applications that may rely on rules, optimization logic, or AI and ML depending on what the use case demands. Cyient applies AI only when it creates measurable, trustworthy, and explainable outcomes.
Through this lens, Cyient’s direction is to bring VISMON AI into Open RAN so that the non-RT RIC becomes the AI policy brain of the network. It learns from network data, shapes intent and guardrails, and communicates these policies through the A1 interface, while the near RT RIC enforces them through xApps operating in tight, safe control loops. This establishes a clear and intentional path toward AI native RAN automation.
Note: 3GPP does not build AI or ML models. Its role is to define shared evaluation methods and frameworks that guide responsible integration of AI into air interface functions.
How and Why
The “how” comes from embedding intelligence into the RAN through the RIC. This enables real time and near real time automated decisions such as traffic steering, energy optimization, and mobility management.
The “why” is driven by network complexity. Multi band, multi-vendor, cloud native RANs cannot be managed reliably through manual intervention alone. AI and ML inside the RIC allow networks to adapt dynamically, optimize continuously, and deliver higher efficiency and performance at scale.
Case Studies
- RIC for Traffic Steering in 5G
A solution provider demonstrated how the near RT RIC receives streams of RAN KPIs and measurements, processes them through AI and ML engines hosted as xApps and rApps, and then makes control decisions that drive traffic steering and load balancing.
The results include improved throughput, more efficient resource utilization, and a better user experience in high mobility or high load conditions. - AI Native Stack for 6G
Next generation 6G networks introduce AI native design. Intelligence will be integrated across hardware, software, and architectural layers.
This AI native wireless stack supports integrated sensing, spectrum agility, and continuous learning across the RAN. It reflects how AI will be built deeper into the network fabric instead of acting only as an optimization layer.
Evolution of Intelligence: 5G ORAN to 6G AI Native Network
Figure 1: AI-based -5G ORAN vs 6G ORAN
| 5G ORAN | 6G ORAN |
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AI and ML are introduced primarily at the RIC layer for the first time. The ORAN Alliance introduced an architecture that includes the RIC, SMO, RIC framework, open APIs, orchestration layers, and AI and ML components designed for near real time enhancements. AI driven applications in 5G focus on:
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AI and ML are distributed across all network components. AI native fundamentals based on deep neural network concepts influence the design of the entire 6G architecture. AI driven applications in 6G focus on:
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Current Challenges and Cyient’s Resolutions
| Challenge | Explanation | Cyient’s Actions |
| Data Quality and Real Time Availability | AI depends on clean, high frequency data. Without reliable telemetry, models cannot perform consistently. | Cyient implements unified data lakes and edge telemetry pipelines to ensure continuous, accurate, and low latency data availability. |
| Multi-Vendor Interoperability | Open RAN involves different vendors and formats, leading to integration challenges. | Cyient adopts ORAN standard APIs, interoperability frameworks, and orchestration practices to support seamless coordination. |
| Model Lifecycle Management and Explainability | Models degrade over time and require trust, traceability, and oversight. | Cyient applies MLOps for versioning, drift detection, explainable AI, and automated retraining within the RIC. |
| Latency and Edge Compute Constraints | AI workloads require compute capacity, which may be limited at the edge. | Cyient uses lightweight AI models, hardware acceleration, and distributed inference closer to DU and RU locations. |
| Security, Privacy, and Governance | AI introduces new risks involving data, models, and compliance. | Cyient enforces secure data pipelines, federated learning, access control, and governance aligned with telecom regulations. |
The Role of Strategic Partners Like Cyient
Cyient brings telecom engineering depth together with software, AI, and automation capabilities to help operators convert ideas into real network value. As a strategic partner in the AI driven ORAN ecosystem, Cyient contributes through five core roles:
- Data Intelligence and Edge Insights
Building unified data lakes and edge telemetry pipelines that deliver reliable, low latency data for analytics and AI.
- Open and Interoperable ORAN Ecosystems
Applying ORAN standard APIs, orchestration frameworks, and automation to ensure smooth multi-vendor integration across RAN layers.
- Continuous AI Lifecycle Management
Using MLOps for model versioning, drift detection, explainable AI, and automated retraining within the RIC.
- Efficient Edge Compute and Inference
Deploying lightweight AI models with GPU or FPGA acceleration so intelligence can operate close to the network edge with minimal latency.
- Secure and Governed AI Operations
Implementing federated learning, secure data pipelines, access control, and governance aligned with telecom regulatory requirements.
Cyient’s work within the Ericsson Intelligent Automation Platform (EIAP) ecosystem reinforces these strengths by aligning them with industry validated architecture patterns, integration models, and automation best practices.
Bringing It Together: Why These Capabilities Enable VISMON AI
Together, these capabilities create the foundation for how Cyient brings VISMON AI into the ORAN environment. With the right data pipelines, interoperability frameworks, lifecycle processes, edge optimisation, and governance already in place, Cyient can operationalise AI inside the RIC in a structured and safe manner, moving from insights to actions with confidence.
This is what shapes the VISMON AI integration path, which progresses through four phases:
Figure 2: VISMON AI + RIC Integration Roadmap
The future of network intelligence will be shaped by how seamlessly AI can work inside open, cloud-native RAN environments. What matters now is not just automating individual functions, but building networks that understand intent, respond with precision, and evolve continuously as conditions change.
By pairing VISMON AI with ORAN principles and the RIC architecture, Cyient is helping create networks that learn faster, operate smarter, and adapt with far greater confidence. The industry is moving toward RANs that are not only programmable, but increasingly self-directed, and this transformation begins with the foundations being built today.
About the Author
Parth is an Automation leader with nearly 14 years of diversified experience across Networks, Technologies, & Domains, and has driven AI/Automation & Digital Transformation initiatives across telecom ecosystems.
As Director of Automation at Cyient, he ideates, architects, develops, and delivers Telecom & Digital solutions with the fusion of Domain expertise, Traditional methodologies, and Next Gen Technologies.
Been passionate about innovation and with a strong focus on AI-Powered Solutions, Network Automation, Analytics & Orchestration, Open RAN/RIC, 5G, Customer Experience, and making 6G-ready architectures, etc., he paved the way for a fully automated, cloud-native network transformation - turning ideas into reality with scalable, production-grade solutions that enable next-generation networks and noticeable business outcomes.