Assessing the market landscape for AI-enabled transport network automation solutions

05 June 2024 | Research

Michelle Lam

Article | PDF (3 pages) | Network Automation and Orchestration

"AI can enhance transport network operations across various use cases."


The emergence of next-generation networking applications is placing new data traffic, capacity and latency demands on transport networks. Operators are investing in transport network automation solutions to support new applications that are driven by API-based networking, multi-cloud network-as-a-service, big data, network slicing and AI/ML technologies. The shift towards open, programmable and disaggregated network architecture that is built on software-defined networking principles has also created a demand for coherent pluggables and open transponders. These new open optical solutions are making it easier for operators to rapidly scale their optical networks and improve service agility.

As network traffic grows and services become more complex, operators will require greater networking capabilities to support the ultra-high bandwidth services and keep up with the vast amounts of data generated by various devices. Operators need enhanced networking capabilities for ultra-high-bandwidth services. Operators will need to invest in transport networks as a priority to reduce operational costs, monetise assets and support new 5G and cloud services. According to Analysys Mason’s survey, the top priorities for transport network investments include reducing maintenance costs, replacing legacy equipment, improving energy efficiency, consolidating network layers and transitioning to open optical transport networks.


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Michelle Lam