As AI, cloud services, and digital platforms push up data volumes, the United States is modernizing its communication networks, gradually replacing copper with fiber optics. Mykola Gomzov — a fiber-optic network design engineer with more than ten years developing telecommunications infrastructure and leading major projects in Ukraine and the United States, and a Senior Member of IEEE — spoke with AI Time Journal about the changes underway in the industry.
You have worked in both Europe and the United States. Where is the potential for telecommunications infrastructure development higher today?
The American market is distinguished by a high level of infrastructure investment and vast territories where network modernization is still underway. This creates steady demand for fiber-optic line construction. In Europe, the infrastructure is generally more mature, and projects are carried out in a more complex regulatory environment. In terms of long-term growth, the U.S. market looks more promising today.
Many say that copper networks are becoming a thing of the past. How quickly will the U.S. be able to fully transition to fiber optics?
This is a long-term process. The scale of the existing infrastructure and the volume of investment required mean the transition could take ten to twenty years. Today the main constraint is not technology but the capital investment needed to modernize the networks.
You research the application of artificial intelligence in telecom. Will it replace engineers?
Quite the opposite. Artificial intelligence is becoming a tool that helps engineers make more precise decisions. AI tools can already be used in route planning, budget calculation, team workload analysis, and project risk assessment. This makes it possible to improve construction efficiency without compromising infrastructure quality.
What in your professional experience has proven most valuable to American employers?
Above all, experience managing full-cycle infrastructure projects — from design to contractor coordination and quality control. International experience helps you adapt more quickly to new requirements and apply a systematic approach to implementing complex projects.
Artificial intelligence is driving unprecedented demand for connectivity and data transmission. How is the growth of AI changing the requirements placed on telecommunications infrastructure, and are today's fiber-optic networks ready for this demand?
AI is indeed changing the requirements for telecommunications infrastructure. Today it's important to develop not only fiber-optic lines but also modern data centers, since they are what handle the processing and storage of enormous volumes of data. At the same time, fiber-optic technology itself is advancing rapidly and is currently capable of meeting AI's growing demands. The key is for network infrastructure and data-center development to move forward in parallel.
You mentioned that the transition from copper to fiber in the U.S. could take ten to twenty years. What are the main technical, economic, or regulatory obstacles slowing this transition?
First and foremost is the high cost of fully replacing copper infrastructure with fiber optics. Permitting is also required, along with coordination with local authorities, since building a new network involves excavation and installation work. In addition, copper networks are still functioning in many areas, so operators aren't always in a hurry to invest in replacing them. Another challenge is a shortage of qualified specialists capable of building and maintaining modern fiber-optic networks. That's why the transition takes considerable time, even as the pace of fiber-infrastructure development keeps increasing.
How is artificial intelligence already changing the way fiber-optic networks are planned, designed, and maintained? Where do you see the greatest opportunities over the next five years?
AI can already help automate network design, analyze large volumes of data, and detect discrepancies faster. It also makes it possible to forecast potential failures and run real-time network analysis. I believe that over the next five years, maintenance costs for fiber-optic networks will drop significantly, since AI will be able to automatically detect problems, analyze them, and pinpoint the source of a fault without requiring large teams of specialists. This will speed up network maintenance and substantially cut operating costs.
As AI applications increasingly run closer to users through edge computing, how do you think network architecture will evolve?
I believe network architecture will become more distributed. More computing power and more data centers will be located closer to the end user, in order to reduce latency and increase data-processing speed. This will require further development of fiber-optic infrastructure, greater network bandwidth, and deeper automation of network management using AI. As a result, networks will become faster, more reliable, and more efficient.
Looking ahead, what changes do you expect to see in the telecommunications industry as AI adoption continues to accelerate?
I expect the telecommunications industry to become significantly more automated. AI will take on the bulk of real-time network monitoring, analysis, and management. This will help reduce operating costs, improve network reliability, and speed up the resolution of issues. At the same time, demand for high-speed fiber-optic networks and modern data centers will continue to grow rapidly alongside the advancement of AI.
How will the profession of network construction engineer change in ten years?
It will remain, but it will become different. Automated systems will gradually take over more and more routine operations, while the engineer will increasingly be responsible for strategic planning, project management, and data analysis. The future of the industry lies in the integration of physical infrastructure with intelligent management systems.
What advice would you give to young engineers who want to work on world-class infrastructure projects?
It's important to continuously develop technical expertise, study industry standards, and build a portfolio of completed projects. It is practical experience, the ability to work in a complex engineering environment, and a willingness to master new technologies that determine a specialist's competitiveness today.
