At the recent Digital Transformation World (DTW) event in Copenhagen, two industry experts came together to discuss the evolving landscape of telecom data monetization and AI integration. Guy Ben-Baruch, Principal Solutions Architect and Domain Lead for AI/ML & Data, Telecom, AWS, and Anshul Bhatt, Chief Product Officer of the OSS Business Unit at Rakuten Symphony, explored how leveraging telco data can drive new revenue streams and enhance competitive advantage.
“The Rakuten Mobile network is advanced enough to extract valuable insights on our users, demographics, network experience and competitor interactions to upskill and upscale our travel services.”
“By unlocking the tremendous value of data residing in the telco network, CSPs can tap into new revenue streams and gain a competitive edge in the market.”
Watch the full interview here
The conversation, moderated by Abe Nejad, Publisher of The Network Media Group, highlighted the immense potential of AI and data monetization in the telecom sector. However, as CSPs continue to explore these opportunities, it is essential to adopt robust data strategies and prioritize security and governance.
The telco ecosphere is rich with data, and this data carries massive untapped potential. Extracting and monetizing this data is essential. Service providers like AWS are collaborating with operators to stream and batch data, providing context for large language models in various AI use cases. Meanwhile, telco innovators like Rakuten Symphony are pioneering efforts to leverage data from deep and shallow packet inspections to improve network planning and deployment and enhance service delivery.
Collaboration between CSPs and cloud providers is necessary to break data silos and create a unified data catalog. With increasing data volumes, analyzing and understanding data correlations, eliminating silos, and developing robust, holistic data strategies are paramount. Proper data strategies and prioritization help avoid cost overruns and inefficiencies.
As networks evolve, including the integration of satellite-based networks, new data monetization use cases will emerge. Network planning will shift from population coverage to area coverage, enabling more remote areas to access network services.
Generative AI implementation, especially as models become smaller and more localized, will make edge computing critical. Complex operations like machine learning will be conducted at the edge, unlocking significant value from network data.
