- Lumen Technologies and IBM are integrating edge computing with watsonx AI to deliver real-time business insights.
- The collaboration aims to accelerate AI adoption at the network edge across sectors like retail, manufacturing and energy.
What happened: Edge AI rollout targets real-time enterprise use cases
Lumen Technologies has partnered with IBM to offer enterprise clients a new edge computing solution powered by IBM watsonx, an AI and data platform. The solution will run on Lumen’s edge infrastructure, which includes over 350 edge nodes across the US, enabling enterprises to run generative AI models and data pipelines closer to where data is generated.
Announced during IBM’s Think 2024 event, the partnership is designed to reduce latency, lower data transfer costs, and enable real-time decision-making for applications in sectors like manufacturing, energy and retail. According to Kate Johnson, CEO of Lumen, “enterprises need real-time processing at the edge to unlock the full potential of AI,” and the collaboration allows them to “train and tune AI models with speed and security.”
IBM’s watsonx will provide tools for building and governing AI models, while Lumen will manage the infrastructure and connectivity. The solution is expected to begin rollout later in 2024.
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Why this is important
The partnership underscores a growing trend of bringing AI to the network edge, where data is generated and immediate response is critical. Lumen and IBM are combining forces at a time when enterprises are increasingly demanding low-latency, high-performance computing solutions to support AI-driven applications. By enabling inference and model training at the edge, businesses can make faster decisions without sending data to distant data centres.
This move positions Lumen to better compete with hyperscalers like AWS and Azure, which are also expanding their edge offerings. IBM, meanwhile, strengthens watsonx’s enterprise reach by embedding it in distributed environments. The partnership also mirrors recent edge AI initiatives such as HPE’s edge AI push and NVIDIA’s collaborations with telecom operators.
The deal makes a strong case for decentralised AI and offers a practical path for large enterprises aiming to operationalise AI outside of the cloud. It reflects a broader shift towards hybrid and edge-native infrastructures to support next-generation automation and analytics.
