Photo By: Denny Müller
The telecom industry does not need more AI hype. It needs a clearer understanding of where artificial intelligence can deliver real business value.
Artificial intelligence has quickly become one of the biggest topics in telecommunications. Operators are exploring generative AI, smarter networks, automated customer service and predictive maintenance.
But one question matters more than the hype:
Where does AI actually create value for telecom operators?
Some of the biggest opportunities are practical. AI can help operators run networks more efficiently, reduce costs, improve customer experiences and create new revenue opportunities.
The key is to focus on outcomes rather than simply deploying AI.
Start with the business problem
Telecom operators manage complex networks and infrastructure while facing pressure to control costs and continue investing in new technology.
That gives them a simple way to evaluate AI:
Can it reduce costs, improve the customer experience or create something customers will pay for?
If the answer is no, the technology may still be interesting. But it becomes harder to justify as a major business investment.
AI should build on the automation and analytics telecom companies already use. It should not become another technology initiative operating separately from the business.
Making networks smarter
Network operations are one of the clearest areas where AI can create value.
Modern networks generate enormous amounts of data about traffic, equipment, performance and customer usage. Historically, much of that information has been used after something goes wrong.
AI creates the possibility of getting ahead of problems.
An AI system could identify patterns suggesting equipment may fail before it actually fails. It could detect unusual traffic, identify capacity constraints or recommend changes as demand shifts across the network.
The value is not the AI model itself. The value is fewer outages, faster problem resolution, better network utilization and less manual work.
Reducing energy costs
Energy is another practical opportunity.
Telecom networks consume significant amounts of electricity, while network demand changes throughout the day and varies by location.
AI can help operators understand those patterns and adjust network resources accordingly. An operator could potentially reduce resources where demand is low while maintaining the service customers expect.
When applied across a large network, even small improvements can produce meaningful savings.
This is the type of AI application that has a clear business case because the results can be measured directly.
Customer service needs to go beyond chatbots
Customer service is an obvious area for AI, but simply adding a chatbot does not necessarily improve the customer experience.
Customers care about getting their problems solved.
Consider someone reporting unreliable internet service. A useful AI system could examine the customer’s account, analyze network conditions and determine whether there is a known issue.
That is more valuable than simply giving the customer another chatbot.
AI becomes more useful when it is connected to the systems that actually run the business.
The bigger opportunity could be revenue
Cost reduction may be one of the first ways operators see value from AI. The larger opportunity could eventually be creating new revenue.
Telecom networks are becoming platforms that can support more than basic connectivity. Operators could offer businesses services based on network performance, reliability, latency and security.
The growth of AI could make those capabilities more valuable.
For example, an enterprise running an important AI application may need reliable connectivity or specific network performance. That could create opportunities for operators to offer differentiated services.
But the industry should be careful. Telecom companies have a history of building technically impressive products that customers were not willing to pay more for.
The starting point should be the customer’s problem, not the technology.
Instead of asking, “How can we sell an AI-powered network?” operators should ask:
“What problem does a customer have that our network and AI can solve?”
AI will also change the network
AI is not only something telecom operators can use internally. Its growth will also create new demands on telecommunications infrastructure.
AI applications require large amounts of computing and data movement. As AI becomes part of more products and services, networks will need to support increasingly demanding workloads.
This creates an important relationship between AI and telecommunications.
AI can make networks smarter, while the growth of AI will create demand for better networks.
A practical view from the industry
The shift from AI experimentation to practical deployment is already becoming part of the work across telecommunications.
Conal Higgins, VP/Field CTO, GTM – Telecommunications at NewRocket, is one example. His work focuses on applying AI across telecom environments, including network infrastructure, OSS and BSS systems, and the connections between them.
His perspective reflects a broader challenge for the industry. A promising AI model is one thing. Connecting it to existing systems and demonstrating measurable improvement is another.
That is where the real test of telecom AI will take place.
Focus on outcomes
The telecom industry’s AI strategy will ultimately be judged by results.
Before investing in another AI project, operators should ask:
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Can it reduce operating costs?
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Can it make the network more reliable?
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Can it improve customer experience?
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Can it reduce energy consumption?
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Can it create a service customers will actually pay for?
AI is an important technology shift for telecommunications. But deploying AI is not the goal.
The goal is to build a telecom business that operates better, costs less and creates more value for customers.
The most important question for telecom executives is not, “What can AI do?”
It is:
“What part of our business could work fundamentally better if we used AI well?”
That is where the real value of AI will be found.