The introduction of 5G has left many customers dissatisfied and the telecommunications industry under pressure.

Despite the promise of an ultra-fast, reliable, and low-latency network with 5G consumers haven’t seen much difference in their service. Telecom operators are now at a critical crossroads of deciding how to gain a return on investment from 5G and create value for customers.

An AI-powered network approach could be one of the ways to generate value for operators. By taking this approach, telecom operators can shift towards creating value beyond just better connection and help enhance operations and service delivery, and reduce costs.

The industry is under pressure and heavily competitive. Here’s how they can meet customer expectations and deliver value with the power of an AI-powered network approach.

1. Tackle faults as they occur

Field operations are often resource-intensive and costly endeavors. It's traditionally reliant on manual planning strategies, which are more reactive in nature. This causes inefficiencies in resource dispatching and unnecessary travel times, which contribute to high costs and have a negative environmental impact.

According to Deloitte, even a two percent reduction in the telco industry’s carbon footprint would result in a potential saving of 12 million tonnes of carbon dioxide equivalent (CO2e). So, how can telco operators turn the tide?

AI is here to fix first-time fix rates

Enter AI-enabled dynamic resource allocation. With assistance from AI algorithms, telecom operators can take an AI-powered network management approach to analyze real-time data to ensure the right technician, with the right skills and parts, is dispatched to improve first-time fix rates.

This proactive approach reduces operational expenses, lowers fuel consumption, and ensures higher customer satisfaction from faster and more accurate service deliveries.

2. Say goodbye to costly asset failures

Telecom operators manage thousands of expensive assets, yet one of the biggest operational risks remains unexpected asset failure, which can disrupt service, damage company reputations, and require costly emergency repairs.

A calendar approach to maintenance has meant operators are spending 40-50 percent more than they need to on asset management. This struggle to assess the health and lifespan of assets leads to premature replacements or unexpected failures.

Never miss an asset issue again

An AI-driven asset lifecycle management approach supported by predictive analytics and the continuous monitoring of real-time and historical data, however, allows companies to assess equipment usage, wear-and-tear patterns, and performance degradation in order to enable predictive maintenance before issues escalate.

These insights are key to helping operators decide when to maintain, refurbish, or retire assets. This shift to just-in-time maintenance means end users aren’t impacted by service interruptions for maintenance, and companies can schedule asset maintenance at optimal times.

3. Always on hand to support workers

Out in the field, technician teams are often reliant on outdated manuals and can’t always tap into institutional knowledge at the moment of need. So how can telco operators do more to support their workers on the front line?

Generative AI is the phantom of all telco knowledge

This is where generative AI acts as a reliable knowledge base. Generative AI models can be trained on internal processes, service logs, and manuals to provide workers with access to on-demand and context-aware support in natural language. Surfacing relevant insights, suggest fixes based on past work order records, and provide step-by-step guidance.

There’s also the training benefit, as new workers can use generative AI to suggest resolutions that more senior members have already logged into the system. This leads to increased productivity, faster resolution times, and the creation of a more autonomous workforce capable of handling complex issues with confidence.

4. Look beyond the hype with intelligent networks powered by agentic AI

With 5G, telecom is addressing the industrial mobility, for which there is a whole range of themes related to the network or how it is used. It also relates to AI taking on new roles as the customer for telecom services (B2AI) or involvement in regulatory processes.

There will also be new AI-led data flows and traffic patterns, which will impact demand for fixed and mobile network capacity and quality. AI agents will be the new subscribers of the network services, and how they use the network can be made much more efficient and different if the agents also have API access to the network and the ability to shape its services as they use them. This is maybe a more futuristic view, but imagine if AI agents both using and maintaining the telecom networks could communicate.

The AI future of Telco

Through integrating AI-powered network management, telecom operators can turn the tide on 5G and start to drive new value.

Those that act quickly and adopt AI will start to see the benefits – from optimized network resources, predictive maintenance, and enhance customer experience. The telecom industries future depends on AI as it not only improves network connectivity, but also presents major opportunities for future growth.