Building a Data-Based Foundation for AI Strategy

Homebuilders have long recognized that the structures they are building depend first on creating a strong foundation. The same can be said of CSPs, only in this case, that foundation takes the form of data instead of concrete. As CSPs look to modernize their IT systems, one of the key goals is to leverage their vast networks and customer data assets to improve operating efficiencies and customer service and create new revenue opportunities. However, that data frequently exists in multiple formats and resides in disparate systems that often don’t talk to each other. Any AI or LLM model is only as good as the data it uses, and one of the key benefits of embarking on a digital transformation is to create a common data platform that can provide the “foundation” for advanced insights. In telecom especially, modern, cloud-native BSS/OSS platforms that can draw from this foundation are central to service provider transformation—supporting everything from service agility and data intelligence to AI integration and ecosystem monetization.

“Once you have the right data, then you can have a very sophisticated and a very advanced AI strategy to take you to the next level,” said Ari Banerjee, Chief Strategy Officer at Netcracker. “Whether you are doing it through Gen AI, whether you're using agentic AI, which is much more autonomous, or you're taking an overall much broader AI strategy, we bring those all together to create the right strategy for the customers.”

That said, CSPs, like companies in other industries, face common challenges. “If you are jumping into AI without thinking about data transformation, without thinking about process transformation, normalization of your systems, consolidation of your duplicate systems and data, then you’re spending your effort on putting AI on top of that kind of messy environment, which is not going to yield good results,” according to Banerjee.

This post from Harvard Business School illustrates the importance of making large-scale organizational changes in smaller parts, warning that companies may face issues such as security vulnerabilities and operational inefficiencies if their data is not handled correctly throughout the process. The only misstep more significant would be to delay the digital transformation process, as the industry landscape is changing more quickly than ever and AI-driven technologies are increasingly more sophisticated.

As a result of these challenges, it is crucial to address the skillset and cultural challenges that prevent more widespread adoption of AI. For CSPs, vendors with the telco-specific insights and experience to help align technology investments with business imperatives can provide a huge boost to AI initiatives and ensure that their BSS/OSS investments can achieve maximum ROI. To augment its modular product portfolio, Netcracker provides a comprehensive suite of business and technology consulting services, as well as an unbroken track record of end-to-end program delivery, to ensure CSPs can extract the most value from their data assets.

Learn more about Netcracker’s suite of cloud-native digital transformation solutions and AI-enabled operations.