Artificial intelligence is rapidly transforming how industries operate, make decisions, and serve customers. As AI and machine learning adoption accelerate, organizations are generating and processing more data than ever before, creating a new era of real-time responsiveness and data-driven operations. At the center of this transformation is connectivity. In dense urban markets like Chicago, where infrastructure is crowded and the margin for error is small, performance and resiliency are critical. Dedicated fiber optic networks are emerging as the foundation of AI infrastructure. These private, high-performance systems provide consistent, high-capacity data movement for everything from AI model training to real-time inference, helping position Chicago as a leader in AI innovation.

Why AI Demands a New Kind of Network

Keeping up with the rising demands of AI takes more than just a fast internet connection. It requires infrastructure designed for speed, scale, and precision, capable of handling vast amounts of data with minimal delay. AI systems rely on extremely low latency, high bandwidth, and the ability to scale quickly as data volumes grow and real-time processing becomes standard.

Shared networks often struggle to keep up, with congestion and performance hiccups that can derail AI applications. Even small delays can have measurable impacts, from slowing financial transactions to disrupting automated healthcare processes.

Dedicated fiber offers a different path. By delivering private, direct connections, it removes the unpredictability of shared infrastructure and allows organizations to maintain consistent performance. Subsurface fiber placement minimizes environmental exposure, protecting critical AI networks from weather, accidental damage, and above-ground congestion. Underground infrastructure also preserves limited urban space, supporting more resilient and redundant pathways in crowded city environments. End-to-end control allows for tailored configurations, ensuring the network can be optimized for the specific requirements of AI workloads. In a city like Chicago, where congestion and complexity are part of the landscape, this control is essential to keep mission-critical applications running without interruption.

How Key Industries are Rebuilding for AI

As the network demands of AI continue to grow, industries are rethinking how they connect, process, and move data.

In finance, ultra-low latency is essential for maintaining a competitive edge. From algorithmic trading to real-time fraud detection and AI-driven portfolio analysis, firms are turning to dedicated fiber routes that offer direct paths to exchanges. When every millisecond matters, the network’s design can be the difference between winning and losing a trade.

Healthcare is also changing fast. AI diagnostics require fast and secure access to imaging and medical records, sometimes across multiple hospital systems. Private fiber networks not only meet compliance requirements but also enable medical teams to share large imaging files in real-time, which can be critical in emergency care situations, such as stroke diagnosis.

In logistics, AI is optimizing everything from delivery routes to warehouse inventory in real time. These applications demand reliable, high-performance connectivity at the edge, ensuring goods move on schedule and operations stay efficient.

Across these sectors, dedicated fiber is no longer optional. It has become a fundamental requirement for AI adoption, supporting both innovation and operational efficiency.

Supporting AI at scale takes more than fast connections. It requires a network built to handle not only north-to-south traffic between users and data centers, but also the growing volume of east-to-west traffic, meaning data moving laterally between data centers, edge sites, and AI endpoints.

Low latency is essential for real-time inference, allowing AI to process data and deliver decisions in milliseconds. High bandwidth enables the transfer of massive datasets used in training and continuous model updates. Without both, AI systems risk bottlenecks that can reduce accuracy and responsiveness.

Purpose-built subsurface fiber infrastructure allows cities to expand capacity without the limits of above-ground congestion, ensuring that AI workloads can scale seamlessly. Buried networks also provide physical security and long-term durability, making them essential for mission-critical AI applications.

As AI workloads increasingly span both centralized and distributed locations, the ability to connect them reliably is critical. Organizations that invest now in diverse, resilient fiber routes will be positioned to handle tomorrow’s AI demands without disruption.

Dispelling Fiber + AI Myths

As more organizations explore AI adoption, several misconceptions continue to surface.

One of the most common is the belief that all fiber networks are the same. In reality, performance varies significantly depending on route diversity, latency optimization, and whether the network is dedicated or shared.

Another misunderstanding is that bandwidth alone determines network readiness. While high bandwidth is important, latency is equally critical, especially for AI applications that require real-time responses. Overlooking latency can result in delays that make AI outputs less effective or even unusable in time-sensitive environments.

Finally, some assume that existing legacy infrastructure can handle modern AI demands. In most cases, it cannot. Purpose-built fiber networks, engineered for redundancy, low latency, and scalability, are increasingly necessary to support advanced AI capabilities.

Shaping the Future of AI Infrastructure

Looking ahead, the cities best positioned for AI success will be those that invest in the right infrastructure today. In places like Chicago, the future of AI depends on dedicated fiber networks that deliver more than just speed. They must also offer reliability, flexibility, and the ability to adapt as AI technology evolves.

By building dense, diverse fiber routes and strategically placing edge aggregation sites near where data is generated, cities and enterprises can reduce latency, improve resilience, and support innovation across multiple industries. These investments will not only prepare them for the digital future but also create a model for how AI infrastructure will develop nationwide.

About the Author

Michael Underdown, President & CEO of Crosstown Fiber, is a seasoned executive with nearly 30 years in the telecommunications infrastructure industry. Prior to his current role, Michael enriched his expertise as the COO of Comdesco Group, Inc., focusing on construction management and consulting for fiber networks and data centers. He also founded and presided over Chicago Fiber Systems, reflecting his dedication to the technological advancement of the industry. Michael’s career is a blend of strategic leadership roles, from operations engineering to new market development in the data center and telecommunications sectors. His acumen extends to real estate, financial consulting, and venture capital, with a keen interest in nurturing early-stage startups and companies navigating pivotal growth phases. Specializing in new market development, real estate, network construction, and channel sales development, Michael melds his broad experience and innovative approach to steer companies toward success.

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