Agentic AI in Telecom
TPR1066 | Expert-Led Live | Automation and Insights | Expert
Course Duration: 4 hours
This training provides a technical overview of Agentic AI and distinguishes it from traditional AI systems. It outlines system architecture and highlights the key features and capabilities of an Agentic system. Students explore several applications in the telecom domain, such as a NOC assistant, network optimization assistant, and customer care assistant. They also identify key challenges and considerations involved in deploying Agentic AI systems.
Intended Audience
Network leadership, Planning, Engineering, and Operations
Objectives
After completing this course, the student will be able to:
■ Define the what and why of Agentic AI and how it differs from traditional AI
■ Sketch the architecture of an Agentic AI system
■ Walk through a few use cases of Agentic AI in telecom such as NOC agent
■ Identify key challenges in deploying Agentic AI in telecom
■ Explore current and emerging trends that may impact telecom landscape
Outline
1. Introduction to AI, ML, and Agentic AI
1.1 Introduction of AI and ML in Telecom
1.2 Evolution from AI to Agentic AI
1.3 What is Agentic AI?
1.4 Traditional AI vs. Agentic AI
1.5 Attributes of Agentic AI - Autonomy, Decision making
1.6 Agentic AI in Telecom
1.7 Knowledge check

2. Agentic AI System Architecture
2.1 Orchestrator, Super Agent, Utility Agents
2.2 Goal-oriented models
2.3 Autonomous decision making
2.4 Knowledge check

3. Agentic AI Use Cases In Telecom
3.1 Network optimization
3.2 Virtual Assistant for NOC
3.3 Customer Service Assistant
3.4 Predictive maintenance
3.5 Knowledge check

4. Key Considerations
4.1 Agentic system interactions
4.2 Multi-agent system and collaborations
4.3 Key deployment challenges
4.4 Current industry landscape of Agentic AI
4.5 Knowledge check