Data analysis for network optimization has been a long-standing industry challenge. However, the integration of native language models and geospatial data is set to transform network planning.
Things previously were just too complex. You were trying to run data sets and come to conclusions on very specific topics or questions, but you may not even be evaluating the right data sets. With generative AI, you’re able to make that interaction with data much easier.
Now, network operators can ask pointed questions, such as where can I put capacity to maximize revenue, uptime or resilience?
Geospatial data adds another layer of insight so that telecommunications providers can fully understand network performance in different environments. With geospatial data, vendors can see that they’re experiencing network volatility in a specific area and analyze terrain, weather conditions, building density and other factors that impact service quality. Providers will be better informed and better able to allocate resources to fix whatever problem is at hand.
With these two technologies at their disposal, telecommunications providers can create digital twins — virtual representations of network infrastructure — offering unprecedented insights into network performance and optimization opportunities.
Read the full report for the rest of my 2025 telecommunications predictions, insights from six other industry leaders and the latest big-picture data and AI forecasts from leaders such as Baris Gultekin, Snowflake’s Head of AI, and Brad Jones, Snowflake’s Chief Information Security Officer.
