With the announcement of a $500 billion AI infrastructure initiative and Microsoft's planned $80 billion investment in data center expansions, the race to build America's AI infrastructure is accelerating rapidly.¹ AI isn't just another tech trend—it's becoming woven into the fabric of daily life, from the algorithms that personalize our streaming services to the chatbots handling customer inquiries. For telecom operators, this shift represents more than just an infrastructure challenge. As AI applications become essential to business operations, network reliability and speed directly impact their customers' abilities to compete in an AI-driven world.
This surge in AI computing is forcing data centers to look beyond traditional hubs. New facilities are emerging in locations like Indiana, Iowa, and Wyoming, where power is more abundant and grids less strained.¹ This geographic shift challenges conventional fiber network planning strategies that were built around connecting population centers and business hubs. For telecom operators, the ability to rapidly extend high-capacity networks to these new locations will determine which AI-powered services their customers can access and how quickly they can deploy them.
These new locations introduce several interconnected challenges.² First is the infrastructure gap—most areas lack existing fiber networks and require entirely new deployments. Second is the time pressure—project schedules demand unprecedented speed in planning and construction to keep pace with AI's rapid evolution. Third is the technical complexity—these networks need higher capacity and redundancy than traditional builds to handle AI's massive data processing requirements. Finally, there's the permitting challenge—working in previously unserved areas means navigating unfamiliar approval processes that can significantly impact schedules.
Power availability is becoming the primary driver of data center location decisions. This marks a significant shift from traditional factors like population density or proximity to internet exchange points.² Network planners must now consider:
Traditional network planning methods—like manual routing and siloed processes—can't keep up with today's deployment demands.¹ Modern fiber planning requires a more comprehensive approach that brings together key technologies. Utilizing advanced GIS tools, planners can quickly evaluate multiple network paths and assess build scenarios in real-time. Collaborative platforms ensure field and office teams work from the same data, while integrated data sources provide visibility into everything from power availability to permit requirements. This consolidated view helps planners identify potential obstacles early and manage multiple project phases simultaneously, significantly reducing time to revenue.²
The AI infrastructure boom will continue to accelerate.² Network operators who embrace modern planning tools will be best positioned to capture this opportunity. Success in this environment requires smarter planning, faster design, and more efficient deployment than traditional methods can deliver.
Modern GIS and design tools can transform months of planning into a streamlined process that matches AI's aggressive deployment needs. Today's fiber network planning goes beyond simply connecting locations—it's about building networks that can scale and adapt to support growing AI infrastructure demands. The technology to make this possible exists today. The question is: are you ready to implement it?
Citations:
1 McKinsey & Company, "AI data center growth: Meeting the demand," January 2025, https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ai-power-expanding-data-center-capacity-to-meet-growing-demand
2 Fierce Telecom, "Trump goes all gas, no brakes on AI," January 22, 2025, https://www.fierce-network.com/cloud/trump-cuts-bidens-2023-ai-safety-order