Unlocking Autonomous Networks with Agentic AI and Amazon Web Services

As 5G networks expand, managing Radio Access Networks (RAN) has become increasingly complex. Operators must:

• Deliver high performance and reliability
• Optimize resource usage in real time
• Adapt to changing usage patterns
• Control rising operational costs

Traditional tools and basic automation cannot keep pace. Without next-level autonomy, operational costs risk becoming unsustainable.

The Goal: Autonomous Networks Level 5

According to TM Forum, autonomous networks progress through maturity stages.

• Level 4: Full autonomy with human oversight
• Level 5: End-to-end autonomy with self-optimization and self-healing

Reaching Level 5 is critical for CSPs (Communications Service Providers) to manage complexity, scale efficiently, and maintain competitiveness.

The Solution: Agentic AI with Amazon Web Services

Agentic AI builds on generative AI by enabling autonomous agents that can:

• Make independent decisions
• Set goals and take actions
• Collaborate with other agents
• Adapt to dynamic environments

In the RAN context, this means embedding AI-driven intelligence directly into the network to enable closed-loop, intent-based optimization—with minimal human intervention.

Why Amazon Web Services?

AWS provides the cloud foundation that makes this possible:

• Amazon Bedrock: Pre-trained foundation models accelerate AI development and deployment.
• Bedrock Agents: Simplify orchestration and complex network workflows.
• High-Performance Infrastructure: Ensures low latency and global scalability.
• Security & Compliance: Enterprise-grade encryption, controls, and certifications meet telecom standards.

Key Capabilities of Agentic AI in RAN

“Talk to Network” Interfaces

Operators can interact with the network in natural language.

Example: Asking “What needs fixing?” generates AI-driven insights, prioritized issues, and recommended solutions.

AI Agent Ecosystem

• Cell Anomaly Detector Agent: Analyzes KPIs to spot issues.
• Root Cause Explainer Agent: Identifies underlying problems.
• Optimization Agents: Adjust parameters (antenna tilt, interference, call quality).
• Supervisor Agent: Coordinates agents, plans strategies, and ensures execution.

From Detection to Resolution

1. Stage 1: Diagnostics – anomaly detection, classification, and root cause analysis.
2. Stage 2: General Optimization – immediate adjustments to improve performance.
3. Stage 3: Specialized Optimization – advanced tuning for antennas, interference, and voice quality.

Visualization & Reporting

AI agents generate text, charts, and reports to communicate clearly across technical and business teams.

Business Benefits for CSPs

80% faster analysis and decision-making → reduces OPEX.

Proactive optimization instead of reactive troubleshooting.

Greater agility → adapt quickly to new demands or events.

Revenue growth → improved network performance drives customer satisfaction and reduces churn.

Secure, scalable operations → built on AWS’s trusted global cloud infrastructure.

Beyond Automation: Redefining Network Management

Agentic AI does more than automate—it redefines network management:

• From human-dependent operations → to AI-driven autonomy
• From isolated decision-making → to coordinated intelligence
• From reactive fixes → to predictive, proactive optimization

This is the final step toward Autonomous Networks Level 5.

Conclusion

Telecom networks are becoming too complex for traditional operations. Agentic AI, powered by AWS, gives CSPs the intelligence, speed, and automation required to achieve end-to-end autonomy while ensuring compliance, performance, and resilience. As an official AWS partner, Softprom helps telecom operators adopt AI-powered automation, reduce costs, and accelerate their journey toward fully autonomous networks.

Contact us to explore how Agentic AI on AWS can transform your network operations.