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Harnessing the Power of GenAI: Transforming CSP’s with Cutting-Edge Technology

Contributed by Sasa Crnojevic, EMEA AIOps Business Principal for Service Providers, SAS.

In the ever-evolving landscape of telecommunications, staying ahead of the curve is paramount for Communication service providers (CSPs). The integration of Generative Artificial Intelligence (GenAI) into telecom, media and technology operations marks a transformative era for the industry, promising a multitude of innovative solutions that can be deployed across diverse domains at an unprecedented pace.

At the TM Forum Inform digital event, which took place in November 2023, insights into the adoption of this technology were discussed among CSP’s with the findings of the report “Generative AI: Operators take their first steps“ revealing real world implementation of GenAI.   The survey found that 57% of CSP’s expect that Gen AI /Large Language Models (LLMs) will have a significant impact on their business in 2024/2025. Additionally, another 37% foresee this impact occurring within the subsequent 2 to 5 years.”

The phases for the introduction of GenAI within CSPs, as outlined in the report, are detailed below. This blog discusses several of these phases, focusing on areas where SAS, as a leading Analytics, Data & AI company, collaborates with its LLM partners.

Figure 1- GenAI implementation plan for CSP’s

 

From enhancing customer service experiences to optimising network operations and driving targeted marketing initiatives, GenAI, coupled with Natural Language Processing (NLP), AI driven decision making, Python, R or SAS code generation assistant and synthetic data generation, presents unparalleled opportunities for CSPs to excel in a competitive market.

 

Network Automation and Optimization:

In an era of rapidly advancing technologies such as 5G and IoT, the complexity of managing telecom networks has reached new heights. Traditional GenAI (asking a question through a chatbot and receiving an answer) does not solve complex business tasks, but it needs to be added in a large and complex process, governed and orchestrated. So GenAI, combined with AI driven decision-making algorithms and processes, offers CSPs a transformative solution for network automation and optimisation.

Figure 2 – Network Automation Flow in SAS

 

By leveraging real-time data analytics Generative AI, with integrated data from both OSS and BSS systems, holds the potential to simplify and streamline these intricate operations, effectively addressing the “needle in a haystack” challenges. Moreover, GenAI facilitates autonomous decision-making, allowing networks to adapt dynamically to changing demands and ensuring optimal performance at all times.

 

Customer Service Reinvented:

Delivering exceptional customer service is no longer a choice but a necessity for CSPs looking to foster loyalty and satisfaction among subscribers. Chatbot, seen in Figure 1, is one of the first services, which is powered by GenAI models. GenAI textual context summarising capabilities, empowered by “Speech to text” and NLP for topics classification and sentiment analysis capabilities, enables CSPs to revolutionize customer interactions through intelligent chatbots and virtual assistants.

Figure 3 – Information flow in Customer Service automation use case

 

These AI-driven agents can comprehend natural language queries, resolve issues in real-time, summarize the context and even anticipate customer needs based on historical data and contextual cues, reacting with the right offer for each customer profile. By analyzing vast datasets, GenAI-powered systems integrated with NLP and AI intelligent decisioning continuously improve their responses, delivering personalized and efficient customer service round the clock.

Meet SAS at FutureNet World 2024, they will be exhibiting the latest AI & Automation solutions.

 

Below-the-Line Marketing Excellence:

In a saturated market, targeted marketing growth and churn prevention initiatives are essential for CSPs to engage customers effectively and drive revenue growth. GenAI empowers CSPs to execute below-the-line marketing campaigns with unparalleled precision and effectiveness.

GenAI enables CSPs to analyze customer behavior, preferences, and purchasing patterns with unparalleled accuracy. Armed with these insights, CSPs can craft personalized offers, promotions, and recommendations tailored to individual subscribers, enhancing customer satisfaction and loyalty.

Figure 4 – Marketing automation flow based on Customer sentiment

 

AI SAS / Python / R Code Generation and Synthetic Data Generation:

The integration of AI SAS / Python / R code generation and synthetic data generation further enhances the capabilities of GenAI, enabling CSPs to unlock new possibilities in data analytics and decision-making.

By automatically generating SAS or opensource code for data analysis and modeling tasks, GenAI accelerates the development and deployment of advanced analytics solutions, empowering CSPs to extract actionable insights from large and complex datasets with ease. GenAI also offers the option of explaining the functionalities or actions of the code, which is already written, to help other programmers to understand it.

Additionally, synthetic data generation enables CSPs to overcome data scarcity and privacy concerns by generating realistic yet anonymized datasets for testing, training, and validation purposes. This facilitates the development of robust AI models and algorithms, ultimately improving the accuracy and reliability of decision-making processes.

 

 Conclusion:

In conclusion, GenAI represents a game-changing technology for communication service providers, offering unparalleled capabilities in customer service, network automation, below-the-line marketing, code generation, and synthetic data generation. By harnessing the power of GenAI in combination with traditional AI in Model Ops lifecycle, CSPs can unlock new avenues for growth, innovation, and differentiation in an increasingly competitive market.

As the telecom industry continues to evolve, embracing GenAI in E2E ModelOps lifecycle will be crucial for CSPs looking to stay ahead of the curve and deliver exceptional value to customers. By leveraging the transformative potential of GenAI, CSPs can pave the way for a future where connectivity is smarter, more efficient, and more personalized than ever before.