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Driving 5G monetization through intent-based network operations

Service providers are racing to monetize on their 5G investments but must overcome key challenges to reap the promise of 5G for their business needs.

White paper

Introduction

It is a well-known fact that service providers need to transform their network operations. Not only are 5G enterprise customers’ requirements the key drivers for this transformation, but service providers’ own business requirements are equally important. Many processes and tasks are still being performed manually and will need to become fully automated to handle the complexity.

AI and automation are key technologies to overcome some of the main challenges associated with operations for 5G and beyond. Therefore, the adoption of an intent-based approach will aid service providers’ transformation from traditional communication service providers to digital service providers.

Hear from Agata Platek, AI Marketing Director and co-author, about the white paper highlights.

Why are intent-based operations key to managing the networks of the future?

Discover the key to monetizing the 5G networks of the future

Opportunities and challenges related to AI-driven optimizations

5G will not only bring a plethora of opportunities for service providers in terms of hundreds of new use cases, innovative business models, B2B/enterprise customers and more, but also some challenges as well. How service providers react and overcome challenges such as complexity of network deployments, monetizing 5G investments, adoption of AI and automation, and network operation transformations will differentiate the leaders from the followers.

Many processes and tasks are still being performed manually and will all need to be fully automated. Today, operations implement AI as individual use cases that are often siloed and purpose-built to their own requirements. While this approach has proven effective on a per project basis, it will fall short in meeting business expectations across a range of important dimensions.

With AI-driven proactive workflows, potential issues can be detected ahead of time and most of them can also be resolved before actual violations occur. This not only reduces network outages and violations but also helps reduce operational cost through AI-driven automations. By using AI to predict, prevent and handle events, opex can be reduced while managing the increased complexity.

How intent-based operations enable long-term business preparedness

An intent-based and AI-driven operation is an automated process that onboards, manages and delivers business requirements provided by the business stakeholders. An operational approach of this sort will transform the operations of tomorrow to align with new and changing business needs and deliver business monetization objectives. The process ensures that an overall desired outcome, comprised of the sum of all requirements, can be achieved using an autonomous and self-organizing operation.

It also provides the structure and clarity of operations required to align resource allocations and processes with the business objectives and priorities, accelerating the go-to-market of competitive offerings as a result. In turn, as the pace of new and changing business requirements increases, the agility and adaptability of operations afforded by intent-based operations will become important drivers for supporting critical business needs.

How intent-based operations enable long-term business preparedness

Conclusion

While AI and automation are key to achieving cost and operational efficiency, service providers must start now to understand, implement, and invest in intent-based operations. For this reason, we at Ericsson believe that for the transition towards intent-based operations, service providers should consider implementing seven key components:

  1. Intent onboarding
    Intent onboarding is a process where business requirements are translated and onboarded onto operations as ‘intent’. In essence, intent captures the objectives described in the business requirement in a well-defined model so that the requirements, goals and constraints are well understood.
  2. Intent handling
    After an intent is onboarded, intent handling is a process that manages the analysis of its state and if it has deviated from expectations. It then formulates a solution that would return it to a state that meets the intent.
  3. Intent delivery
    Intent delivery is a process that plans the execution of all solutions from multiple intent handling streams. Each solution provides a set of actions specific to its intent handling and includes contextual information such as priorities and task execution time as well as time to violation.
  4. Autonomous and self-organizing platform
    Intent-based operation relies on an autonomous and self-organizing platform that provides the capability needed to operate an intent.
  5. Knowledge Base
    The effectiveness of an intent-based operation first and foremost depends on the knowledge base in the system. The knowledge base stores curated knowledge objects that represent everything the system knows.
  6. AI agents
    An AI agent is a ‘worker’ programmed to execute a certain task. The AI agent may have reasoning capabilities that, when given access to a knowledge graph, can draw conclusions based on certain reasoning techniques such as backward chaining or constraint solving.
  7. Intent management
    Intent management provides the necessary framework, including data models, for an intent-based operation to operate on the system. The framework provides a structure as to how an intent is understood and processed throughout the system.

Due to the expected scale, complexity, and criticality of future networks and use-cases, implementation of intent-based operations will be the way forward for service providers in terms of differentiation and helping them to monetize their investments.

Driving 5G monetization through intent-based network operations

AI Artificial Intelligence

ARPU Average Revenue Per User

CSP Communication Service Provider

eMBB Enhanced Mobile Broadband

FWA Fixed Wireless Access

KPI Key Performance Indicator

ML Machine Learning

MR Machine Reasoning

NOC Network Operations Center

NPS Net Promoter Score

SLA Service Level Agreement

URLLC Ultra-Reliable Low-Latency Communication

Authors

Jia You

Jia has over 20 years of experience in the OSS industry and successfully incubated products in the AI/ML, Service Assurance and Analytics domains. He is currently leading innovation in the areas of 5G AI and automation for Ericsson Managed Services.

Rajat Kumar Kochhar

Rajat has 16+ years’ experience in telecom, with roles in R&D, Managed Services, Business Development and Pre-Sales. He is a Senior Specialist at Ericsson for 5G test tools architecture and design.

Agata Platek

Agata is Marketing Director at Ericsson. In her current role, she works with strategic topics of AI and automation across Business Area Managed Services. She is also the host of the Ericsson AI Operations podcast series.

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