AI is Reshaping Global Secure Connectivity

The AI revolution isn’t just about bigger models and smarter applications.  It’s also about the network infrastructure that enables them. As AI evolves, service providers must rethink their architectures to deliver the future of global secure connectivity.  What was impossible just months ago will soon be the baseline expectation for customers going forward. The pace of innovation is truly astounding, and now is the time to be investing in the innovations that will power this new world..  

At the heart of how Service Providers are evolving their architectures are the unique requirements of AI services and experiences. Here are a few key areas where AI is reshaping how networks are designed and operated. 

Training: The Need for High-Bandwidth, Low-Latency, Power Efficient Networks

AI training workloads are growing, and so are the size and distribution of training clusters. Web-scale providers are now spreading clusters across metro regions, requiring high-bandwidth, low-latency connectivity to maintain performance. 

• Traditional, centralized network architectures won’t scale—distributed and edge-based architectures will be key. 
• Networks must keep pace with AI models that demand real-time data exchange across wider geographies. 

Inferencing: A New Paradigm of Dynamic, Multi-Cloud Traffic 

AI is shifting from static, single-location inferencing to dynamic, distributed inferencing across multiple clouds. Techniques like Test-Time Compute (where models “think” more during inference) will demand massive amounts of real-time data exchange across models. 

• Expect more smaller models, working in sequence to refine results. 
• AI-driven data flows will become less predictable and highly adaptive. 
• AI inference traffic will increasingly move upstream, placing new demands on network design. 

Agentic Applications: The Rise of Multi-Agent AI Traffic 

AI-driven agentic applications, where AI agents collaborate dynamically, are introducing entirely new traffic patterns. These apps will create latency-sensitive, east-west traffic across distributed clouds as agents communicate in real time to complete tasks. 

• AI-generated data won’t just be flowing in one direction; networks must handle multi-directional patterns. 
• Service providers must rethink traffic management to accommodate these adaptive, multi-agent workflows. 

To stay relevant and lead through this transformation, Service Providers must adapt their network for the onset of AI.  There isn’t a perfect playbook written yet, and we know many of you are just starting to shape your strategy, but here are a few actions you should all be taking today:  

1. Build a Resilient, Distributed Architecture 

• Move compute closer to the edge to reduce core network congestion. 
• Handle unpredictable AI traffic patterns with distributed data processing. 
• Reduce latency by delivering AI services closer to users. 

2. Adopt Intelligent Routing 

• Traffic in the age of AI  needs more than a simple, high-bandwidth connection—it needs a smart, telemetry-driven network. 
• Embedded intelligence will enable high-speed, low-power connectivity across wide geographic areas. 

3. Embrace Convergence 

• Converging IP and optical layers simplifies operations and lowers costs. 
• Pluggable optics replace traditional optical systems, delivering high-bandwidth, long-haul connectivity while reducing complexity. 

This isn’t just hype. Service Providers that embrace AI will see tangible benefits, including increased revenue, cost reduction, and enhanced customer experiences.  For example, by hosting AI inferencing infrastructure and leveraging underutilized fiber and points of presence (PoPs), providers can generate new revenue streams. Additionally, monetizing network slicing by offering latency-sensitive AI traffic guarantees with service-level agreements (SLAs) further boosts profitability.  On the cost side, deploying edge AI compute requires efficient connectivity, and converging IP and optical networks can significantly reduce expenses.  Meanwhile, AI-powered automation and observability ensure reliable, high-performance connectivity, while AI-driven network planning and troubleshooting help prevent faults before they occur, leading to a seamless and improved customer experience. 

Cisco is committed to building AI-ready networks with our Service Provider partners and is offering much of what is needed for an AI-driven future.  We provide and developed tools for Service Providers to handle new traffic patterns, monetize AI, and drive operational efficiency.  

For example, our new Cisco’s Agile Services Network (announced at Cisco Live in Amsterdam a couple of weeks ago) enables Service Providers to efficiently manage AI-driven traffic patterns. And today at Mobile World Congress we have added new assurance capabilities that include real-time visibility into on-network and off-network connectivity, allowing Service Providers to build resilient, profitable AI-ready home and mobile subscriber experiences.  

The AI era is here.
The question is: Is your network ready? 

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