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BSS/OSS integration will be critical for telecommunications operators to reap the full benefits of this transformative technology.

By Ari Banerjee, senior vice president of strategy, Netcracker Technology

Telecom operators face intense competition and pressure to transform. Many seek emerging technologies like generative AI (GenAI) to increase productivity, boost revenue growth and enhance customer experience. However, realizing the full potential of GenAI in telecom requires capabilities that address challenges unique to our industry.

The transformational power of GenAI is its ability to create contextual new content, which is made possible by training neural networks on enormous volumes of data and applying techniques that help AI models understand what to focus on. With these mechanisms, a generative AI system can identify word patterns, relationships and the context of a user’s prompt.

Companies that invest in using specialized or proprietary data – such as BSS/OSS data – to enrich GenAI models can achieve a significant competitive advantage over generic, publicly available Gen AI tools.  

So how will this impact the telecom industry?

GenAI has the potential to significantly increase telco productivity across the business and make leaps in customer experience, especially in customer care and sales and marketing. For example, chatbots will become an exceptional front end tool, as they can discuss issues and requests with a more personalized approach using customer data and details. Agents will have their own personal assistant that is able to find data from knowledge bases and quickly guide them to more accurate responses.

From a marketing perspective, GenAI can create new and personalized content much faster, such as articles, blogs and social media posts, and can provide better advice on customer requests to close a sale. On the operations side, GenAI solutions will be able to provide streamlined configuration; smarter recommendations; simplified network planning, installation and configuration and a faster learning curve.

Overcoming GenAI Challenges

However, as with every emerging technology, there are many challenges associated with the widespread use of GenAI – especially its use in the telecom industry—which will require new thinking and approaches. The first one revolves around getting access to proprietary telco data without violating privacy laws. As one of the most significant impacts of GenAI will stem from its ability to quickly run through customer data sets and utilize the information for custom content, there is a need to protect personally identifiable information. Telcos must also ensure that they are protected from security threats made by those using GenAI to infiltrate their systems, and they will need to keep up with a constantly changing data set rather than just fine tuning data in real time. In addition, a large proportion of telco data changes constantly, creating challenges for operators to leverage real-time data to deliver exceptional value and productivity gains.

Along with privacy and security concerns, other challenges surrounding the use of GenAI include an overestimation of the technology’s capabilities. GenAI utilizes data it receives to produce content, but its abilities are imperfect in the sense that it can misconstrue facts and generate incorrect information. Large AI foundational models are also very costly to implement and require a significant amount of training in order to ensure they work properly for a telco’s internal processes.

Despite these challenges, telcos are making moves toward bringing GenAI into their businesses. But to make the most of GenAI functionality, they will need to rely on the data provided by their BSS/OSS systems for training and ongoing problem solving. GenAI will need telco BSS/OSS integration to be truly revolutionary. In fact, about 90 percent of telco GenAI use cases will require this integration, including care digital assistants, personalized sales assistants, catalog configuration, hybrid RAN configuration and more.

Netcracker recently launched its GenAI Telco Solution, a pioneering solution that bridges the power of generative AI models with the valuable telco BSS/OSS data and business knowledge. It sits at the intersection of the generative AI models, the users (customers, partners, telco business and operations staff) and the highly valuable yet sensitive telco BSS/OSS data. With this solution, communications service providers (CSPs) can harness their valuable telecom data and knowledge in a secure and controlled way to bring exceptional benefits to customers, partners and their own businesses. This includes support for specialized telco-centric scenarios such as Care Assistant, Agent Partner, Sales Assistant, Catalog Assistant and Digital Operations Technician.

Some of the most immediate applications are likely to be the use of billing and usage data for personalization of marketing materials and product recommendations; improved chatbot functionality through additional context; history and insight provided by billing, usage data, data stored in inventories, order management tools and other BSS/OSS repositories; and generation of synthetic data for better predictive modeling and improved anomaly detection.

Harnessing GenAI and BSS/OSS for Business and Operational Improvements

GenAI will improve IT business and network operations in the following ways to deliver value and productivity gains to telcos:

  1. Lowering costs: Telcos will be able to decrease customer support costs without compromising quality of experience. This includes improved first contact resolution, better time to resolution and reduced cost per contact. On the network and business operational side, telcos will require fewer technical staff and staff needed for their user interface and business processes.
  2. Supporting provisioning and troubleshooting: GenAI has the potential to be highly useful for workforce assignment and dispatch to customer premises by offering virtual assistants that provide real-time support in provisioning and maintenance. GenAI can provide troubleshooting assistance to premise-based network problems, which can be further personalized based on intelligent customer segmentation.
  3. Increasing revenue: Telcos will gain a faster time to value through rapid creation of business ideas in BSS (offers, promotions and discounts, for example), quicker sales conversion and faster design and testing of new services.
  4. Improving prediction and optimization: The generation of new data sets also has a wider implication in the training of predictive models and improving optimization of systems. GenAI can produce synthetic data to improve a sparse data set for model training for predictive maintenance or in the detection of unusual calling patterns indicating fraud.
  5. Procurement and Purchasing: GenAI has been used in other industries to generate and process requests for proposals/information (RFPs/RFIs) and purchase contracts. If adapted with telco-specific information (through retrieval augmentation, fine-tuning, or other non-GenAI ML capabilities), GenAI can accelerate RFP evaluation and approval processes.
  6. Network Operations: Automating monitoring, predictive incident response, and network planning with GenAI can cut critical network incidents and reduce the time to design and provision new network services.
  7. Delivering a superior customer experience: Telcos will find that using GenAI to pull data from their BSS/OSS will result in higher net promoter scores, customer satisfaction and customer effort scores.

The Netcracker GenAI Telco Solution's focus is to help service providers to securely tap into their telco data and maximize the value from multiple GenAI models and platforms. Netcracker's solution addresses the data privacy, security and quality concerns when leveraging enterprise telco data with public and private GenAI models allowing service providers to quickly generate tangible business value from GenAI for their customers and their internal operations.

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