By Ari Banerjee, Senior Vice President, Strategy, Netcracker Technology 

Generative AI has the power to transform the telecom industry, but first communications service providers must overcome challenges to take advantage of its full potential.  

Though generative AI (GenAI) is transforming the telecom industry, realizing the full potential of this emerging technology is not without challenges. For instance, the proprietary BSS/OSS data needed to create value-based GenAI use cases is protected by privacy laws. Combine that with data security concerns, dynamic data sets, the cost to implement large AI foundational models, as well as other challenges, and onboarding GenAI isn’t as straightforward as merely flipping a switch. 

GenAI Challenges Explained 

Like any emerging technology, there are challenges associated with using GenAI – this is especially true for the telecom industry. The first and most significant revolves around accessing sensitive proprietary telco data without violating privacy laws. Additionally, much of the data required, such as usage and inventory, is dynamic – changing in real-time. Since this data isn’t static, it makes it unsuitable for the fine-tuning techniques required to build GenAI models. Additionally, telcos need to ensure that they are protected from security threats made by those using GenAI to infiltrate their systems. 

Along with privacy and security concerns, CSPs face other challenges, such as overestimating the technology’s capabilities. To produce content, GenAI uses the data it receives, however Large Language Models (LLMs) such as ChatGPT do not know the telco business and its processes. Since the input is ambiguous and not tuned to the specifics of the industry, there’s a distinct possibility that GenAI will misinterpret facts and generate inaccurate information.  

Lastly, LLMs are costly for telcos to build in-house and incur significant running costs across vast computing resources. By some estimates this could cost telcos upwards of $700,000 a day, making this investment prohibitive for many.  

To overcome these challenges, operators need new approaches to mediate between different types of GenAI models, users, and telco data. 

Unlock the Power of GenAI 

To make a significant impact, approximately 90% of the industry’s use cases require access to sensitive and proprietary telco data, making integration with BSS/OSS a necessity. To help CSPs overcome challenges and unlock the true power of GenAI, Netcracker recently launched its GenAI Telco Solution.  

The GenAI Telco Solution comprises a GenAI Telco Platform consisting of knowledge management to build, test, and optimize telco-focused scenarios such as customer care, business operations, sales, and network operations. It includes a GenAI Trust Gateway that integrates with the telco IT and data analytics environment, works in real-time to create personalized prompts to ensure high-quality GenAI interactions, and conceals sensitive telco data, providing CSPs with the highest levels of security and accuracy. 

This solution securely connects the power of GenAI with telco BSS/OSS data, enabling operators to maximize the value gained from multiple GenAI models and platforms. And, since GenAI models are typically unaware of industry specifics, the GenAI Telco Solution bridges the gap by providing the GenAI model with specific knowledge and data related to the telco business. It educates GenAI models to understand the telecom business by rationalizing interactions through intent recognition, search, retrieval, reasoning, and fine-tuning capabilities, improving interaction quality and performance. 

By harnessing the power of GenAI in conjunction with BSS/OSS data, operators will benefit from:   

• Lower costs: GenAI and BSS/OSS will enable CSPs to reduce customer support costs while improving the quality of customer care. These benefits are derived from improved first-contact resolution, quicker time to resolution, and reduced cost per contact. On the network and business operational side, technicians will be able to complete jobs faster. This efficiency will result in operators requiring less technical staff.  
• Improved support of provisioning and troubleshooting: Digital assistants will deliver real-time support for provisioning and maintenance. The technology can also provide troubleshooting assistance for premise-based networks, which can be personalized based on intelligent customer segmentation.
• Increased revenue: The rapid creation of business ideas such as offers, promotions, and discounts, along with the ability to close deals faster and quickly design and test new services will enable CSPs to improve time to value.
• Improved prediction and optimization: GenAI can produce synthetic data to improve sparse data sets for model training of predictive maintenance or the detection of unusual calling patterns that could indicate fraudulent activity.
• Enhanced customer experiences: The data GenAI pulls from the telcos’ BSS/OSS will result in higher net promoter scores, enhanced customer satisfaction, and improved customer effort scores.