Advancements in GenAI for Enhanced O&M and Computing Optimization

The previous blog analyzed the exciting advancements and potential use cases of telecom operators adopting Generative AI (GenAI). While that post offered a broad perspective, we’re particularly interested in diving deeper into two award-winning TM Forum Catalyst projects that showcase significant practical benefits for the industry. These programs not only highlight the critical challenges operators face but also demonstrate how GenAI can deliver impactful solutions, focusing on generating new revenue streams and boosting efficiency through cost reduction. Let’s explore how these catalyst programs pave the way for these improvements.

GenAI for Autonomous Networks Operations and Maintenance

Among various ongoing efforts to enhance cost reduction and efficiency through GenAI, TM Forum’s “GenAI for Autonomous Networks (AN)” stands out as a critical project. This catalyst received the Best Moonshot Catalyst – Attendee’s Choice Award at the recent TM Forum awards. The project aims to integrate GenAI into Autonomous Networks Operations & Maintenance (O&M) to enhance automation and intelligence.

This project includes modules that perform intelligent analysis, decision-making, and intent understanding. These capabilities enable operators to improve O&M efficiency by focusing on experience awareness and execution, ultimately resulting in cost control. Specific applications include:

• Core Network Complaint Analysis: Utilizes GenAI for intelligent analysis of signaling, improving complaint handling accuracy and efficiency.

• Transport Network Troubleshooting: Employs GenAI for intelligent decision-making, enhancing automation and interaction experience in network issue troubleshooting.
• HBB Installation and Maintenance: Implements GenAI for intent understanding, assisting engineers with installation, maintenance, and troubleshooting through natural language interaction and knowledge databases.

• Wireless Network Optimization: Enhances data analysis capabilities, providing deeper insights into network performance and customer behavior, leading to more effective optimization strategies.
• Intelligent Charging Management: Improves intent understanding, enabling intelligent configuration and recommendation of charging systems, thus shortening the service monetization period.

GenAI for Intelligent Allocation of Computing Power and Revenue Efficiency

Another award-winning catalyst, recognized as the Outstanding Catalyst – Innovative & Futuristic, explores how GenAI can assist in the intelligent management of computing and networking resources. This catalyst seeks to deliver a computing resource service driven by intent and powered by Generative AI and automation.. By intelligently detecting resource requirements, it allocates computing resources accordingly, ensuring optimal efficiency and user satisfaction. This revolutionary use case captures a CSP customer’s business intent verbally or textually from a CSP customer and provides appropriate solutions based on the initial conversation.

The catalyst has developed an AI-native Computing Force Network (CFN) operation system, enabling CSPs to schedule computing and network resources across cloud-edge environments efficiently. It offers a one-stop experience for customized large language model (LLM)–based intelligent business applications. The impacts are significant for customers, CSPs, and partners:

Customers

• Time to Market & Total Cost: Enterprises can quickly and economically access intelligent applications, launching services in minutes by discussing business scenarios with CSPs, reducing R&D time by 60%.
• Cost-effectiveness: Ordering services through a CSP can save 30% on hardware and 50% on high-level labor costs compared to individual procurement.

CSPs

• Revenue and Profit Growth: Each CFN business can generate $1-3 million in revenue, with potential for significant growth through service scaling.
• Operational Capacity Improvement: Enhances CSPs’ operational autonomy from L1.6 to L3.6, automating 60% of processes, increasing resource utilization by 40%, and reducing operational costs by 50%.

Partners

• Business Model Innovation: Precise matching of customer needs with CFN integration enhances revenue.
• Complexity Reduction: Allows partners to focus on specific domains without considering integrated business complexities.

Conclusion

GenAI has primarily served as a chat assistant, generating content based on large language models (LLMs), either generic or domain-specific. However, GenAI’s future potential in the telecom and communications sectors extends far beyond these initial applications. As demonstrated by the TM Forum catalyst projects, GenAI is poised to revolutionize the industry by enabling unprecedented levels of automation, intelligence, and efficiency.

These are just two catalyst programs discussed in this article. In upcoming posts, we will explore more innovations in this space.