Where Agentic AI Meets the Network Edge
What a difference a quarter makes. Since our mid-year CTP update, agentic AI has moved to the forefront of the AI conversation. Granted, there’s much hype out there. But there’s also an underlying rumble heralding real change for enterprise users. And with this trend, the network edge becomes a key focal point.
There are several reasons for this. First, emerging AI applications feature reasoning as a central feature. And reasoning agents require user interaction, which is available at the network edge, where we see smartphones, IoT devices, cameras, ATMs, and other points of contact with AI applications. The edge is also the fastest route to end-device or user input and the place where it makes sense to process massive amounts of data produced by sensors, smartphones, etc. Privacy and security also factor in.
Agentic AI therefore requires edge AI. And the edge requirements call for a shift in architecture. Sophisticated data processing at the edge is needed to make sense of the enormous volume and variety of data produced by end-devices. But let’s be clear: A multi-layered approach is needed, in which devices interact with gateways and servers, which in turn link through a distributed network layer to the cloud or datacenter that manages model training, analytics, global orchestration, and updates.
What all this means for enterprises is more scrutiny of emerging technologies offered by a broadening range of vendors, including the leading public cloud providers as well as service providers such as Equinix and Lumen, CDN companies such as Akamai, and solutions from firms like ZEDEDA.
In our latest Cloud Tracker Pro Update report, “CTP 3Q 2025 Update: The Edge: AI’s New Frontier,” we take a closer look at these points, as well as scope out the latest capex reports from the leading hyperscalers (including Oracle) and telcos. We also examine the issue of OpenAI’s position in the middle of big and controversial infrastructure investments by the public cloud providers and others.
CTP subscribers, click here to view the full report!
We also look at the progress of AI in vertical markets, examining the specific benefits cited by enterprises as reported in our Enterprise AI Index of over 160 case studies of successful AI adoption. Retail, financial services, and healthcare continue to dominate the landscape.
Bottom line? AI continues to have a major impact on enterprise customers, and though agentic AI remains in many ways a work in progress, it’s taking root in enterprise plans. Distributed data management and accelerated architectures are central to the success of this new world of agents. Inter-agent communication across multivendor environments remains a big issue, with the Model Context Protocol begging for standardization and security features. Lots to watch. Stay tuned!
