The projected value of the global machine learning market by 2030

The projected value of the global machine learning market by 2034

( MarketsandMarkets)

THREE PRACTICAL APPLICATIONS OF MACHINE LEARNING

Smart Manufacturing and Logistics: Within the controlled environment of a factory or warehouse, private 5G networks offer unparalleled reliability and security. Here, ML algorithms can analyse data from thousands of IoT sensors on machinery to predict equipment failure before it happens, minimising costly downtime. Computer vision models, powered by edge computing, can perform automated quality inspections on assembly lines with superhuman speed and accuracy.

Smart Cities and Infrastructure: For urban environments, ML helps make sense of the vast amounts of data generated by city-wide sensors. It can be used for intelligent traffic management to reduce congestion, predictive maintenance on public utilities such as water and energy grids and enhancing public safety through smart surveillance. For instance, Hitachi’ s Intelligent Infrastructure Monitoring( HIIM) solution utilises an AI-driven architecture to modernise the monitoring of critical assets, such as energy substations.

Edge Computing and Analytics: Many emerging applications, such as autonomous vehicles or augmented reality, cannot tolerate the delay of sending data to a centralised cloud for processing. Edge computing solves the problem by bringing computational power closer to where the data is generated. For telcos, it presents a significant opportunity. By offering AI-enabled analytics at the network edge, they can support low-latency use cases, such as real-time video analysis for crowd management at events or instant threat detection in secure facilities.

152 November 2025