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Beyond the Hype: The Transformative Role of GenAI from Customer to Network & Service Operations

Contributed by Carla Penedo, Director of Offer Development & Innovation, Celfocus

In the ongoing journey of Artificial Intelligence (AI), the past year has witnessed a remarkable surge of interest in GenAI, marking it a pivotal focus for numerous companies. This technology has become a beacon of hope for many Communication Service Providers (CSPs) seeking reinvention. While traditional AI applications progressed slowly, often met with hesitancy due to their reliance on probabilistic outcomes, the advent of GenAI has shattered the notion that absolute certainty is a prerequisite for utility. Now, it stands as a groundbreaking advancement, positioned alongside the Internet in terms of significance.

Primarily, companies are investing in GenAI to enhance customer experiences and drive internal efficiencies. However, as business complexities escalate, particularly within network operations, the need for proactive and predictive analytics emerges as a critical driver. Despite the promise, scepticism still looms among network operations teams regarding the new and unproven network capabilities of GenAI, reflecting a broader aversion to risk.

Carla is presenting a case study – GenAI in Telco Operations: A Gamechanger? – at FutureNet World on the 16/17 April in London

Although production use cases remain sparse, early implementations of GenAI have already showcased potential advantages in various areas, with a strong emphasis on enhancing customer experiences and starting to address challenges within network and service operations. Drawing from our experience at Celfocus, let’s now highlight the use cases that are demonstrating the most value and potential for further advancement.

 

Enhancing Customer Operations with Personalisation at Scale

In today’s digital landscape, customers expect personalised experiences tailored to their preferences and needs. GenAI enables telcos to achieve this by analysing vast datasets and delivering targeted services and support. The top use cases where we have seen proven value include:

  • AI-Powered Chatbots: GenAI-driven chatbots engage with customers in real-time, providing instant assistance, resolving queries fast, and improving overall satisfaction.
  • Deep Detractors: GenAI uses sentiment analysis to identify deep detractors, pinpoint reasons for dissatisfaction and propose retention strategies.
  • Predictive Analytics: By leveraging GenAI algorithms, telcos can anticipate customer behaviour and preferences, enabling proactive outreach, personalised recommendations, and campaign effectiveness.
Figure 1 – Customer Operations use cases.

 

Optimising Network & Service Operations with Proactive Network Intelligence

Telcos manage extensive networks comprising various elements that require constant monitoring and optimisation. GenAI empowers telcos to get closer to the aspiration of autonomous networks with insights and automation capabilities to streamline network operations and enhance performance.
Through the correlation of multiple data inputs, the process of identifying problems is accelerated, leading to faster resolutions and, where relevant, the proactive detection of issues before they become apparent to the user. Some use cases are also beginning to stand out, leveraging GenAI to bring more efficiency, service improvement, and cost optimisation to network and service operations. These include:

  • AI Network: By using GenAI capabilities in natural language processing to detect anomalies and improve network and change management performance.
  • Service Operations: GenAI can analyse customer feedback, network performance metrics, and service usage to identify areas for improvement. It can recommend actions to resolve issues more effectively.
  • Engineering Assistant: GenAI can add more interactivity and dynamism to existing networking tools through a conversational interface that assists in daily work.
Figure 2 – Network & Service Operations use cases.

 

From Vision to Reality: Navigating the Deployment Maze with GenAI

Transitioning from GenAI proofs of concept to production deployments in telecommunications requires overcoming challenges. Despite successful trials, there’s a modest number of actual deployments, highlighting a gap in implementation. Articulating the value proposition for GenAI remains a challenge, necessitating alignment with broader business strategies to drive tangible outcomes.

Key pillars when moving from proofs of concept to production environments include defining a robust business case, setting a proper data strategy, and implementing an effective cost strategy.

Figure 3 – Key pillars to move towards GenAI production deployments.

 

  1. Business Case: The success of GenAI in telco operations hinges on the ability to articulate a compelling business case. This entails establishing clear objectives, quantifying potential benefits, and aligning with organisational goals. Telcos must thoroughly evaluate ROI, considering factors such as cost savings, revenue generation, and enhanced customer satisfaction.
  2. Data Strategy. A pivotal factor for successful GenAI production deployments lies in the fine-tuning of models to process large volumes of proprietary data effectively. Ensuring data quality and preparing the data infrastructure to accommodate this need are crucial. Operators must prioritise easy access to data across the organisation for scalable AI deployment, alongside implementing an AI governance program to mitigate technical debt and encourage experimentation.
  3. Cost Strategy. To effectively manage expenses and optimise resource utilisation during deployment, operators should embrace cost-effective approaches. This entails implementing strategies to monitor and control cloud spending, ensuring efficient allocation of resources. Furthermore, to deploy AI at scale and industrialise deployments, operators must integrate Machine Learning Operations (MLOps) and FinOps practices. This approach, akin to the transformation seen in the software sector with DevOps, enables streamlined operations and maximises the value derived from AI initiatives.

 

Concluding Remarks: Mastering GenAI the Right Way

As telcos embark on their journey towards digital transformation, GenAI emerges as a powerful enabler, offering unprecedented opportunities to enhance customer experiences and efficiency. However, amidst the hype, there lurks the danger of overconfidence, leading to its misapplication in areas beyond its competence. At Celfocus, we prioritise understanding the core business problem before selecting technological solutions. This approach ensures that our technology choices effectively address real-world challenges, harnessing the hybrid power of standard AI models and GenAI solutions. In our specific approach to GenAI, we emphasise:

  • Identifying the value proposition by assessing efficiency gains, cost savings, and service enhancements as a starting point.
  • Proving the concept first to validate the alignment of the use case with GenAI, scaling, reducing costs, enhancing resource efficiency, and improving end-user experiences.
  • Driving agility by continuously learning and adapting to GenAI’s evolving capabilities.

In essence, the key mantra is to drive value, innovate, and rapidly adapt with GenAI.

 

To learn more about Celfocus GenAI, click here.