The telecommunications industry, currently valued at £35.9 billion, is at a critical crossroads. The rollout of 5G networks promised ultra-fast speeds, low latency, and high reliability, yet, unlike previous network iterations such as 3G and 4G, consumers are seeing very little difference in their service. Telecom operators are faced with the challenge of how to monetise their 5G investment and create value from existing revenue flows. An AI-powered network management approach will be a key competitive differentiator, argues Markus Persson, Global Industry Director of Telecoms at IFS. Telco organisations will be able to dynamically allocate resources, spot potential network issues, empower field workers with GenAI, and exploit Agentic AI to reshape the future of intelligent networks.
The Covid-19 pandemic changed everything in the telecoms industry. Overnight, everything moved online, and companies had to deal with sudden demand for remote working and video conferencing services. In the UK, private telco services suppliers saw a dramatic uptake in business from public services and large organisations transferring to remote work. So, what’s changed?
Now, consumers are dependent on the need for reliable networks. They expect seamless connectivity everywhere. With 3G and 4G, the mobile internet became real and was a significant change in people’s lives, but now with 5G, consumers only see more of the same, just faster.
Communications service providers (CSPs) were not offered new services to sell, and the fear of losing subscribers is what is keeping investment levels up. Everybody takes connectivity for granted and it’s assumed that consumers will pay for not losing it rather than paying for additional services.
In 2025, the telecom industry is at a crossroads. With an AI-powered approach to network management, telecom operators have every opportunity to shift towards creating new value beyond traditional connectivity, to optimise operations, reduce costs, and enhance service delivery.
It’s a competitive industry with many suppliers, all only too aware of the job they have to do to meet consumer expectations and not lose subscribers. Here’s what they have the power to deliver.
Don’t wait to resolve faults in progress
Field operations are often resource-intensive and costly endeavours. Traditionally, the act of dispatching technicians, sourcing parts, and planning routes has relied on manual planning strategies, which are more reactive in nature. For instance, if a fault is detected, normally by the customer, a human operator goes out to fix the issue in person. This causes inefficiencies in resource dispatching and unnecessary travel times (especially if technicians make repeat site visits), which contribute to high costs and have a negative environmental impact.
In fact, according to Deloitte, while telecommunications does not contribute towards global emissions at anywhere near the levels of the aerospace or media industries, even a 2% reduction in the telco industry’s carbon footprint would result in a potential saving of 12 million tonnes of carbon dioxide equivalent (CO2e). That’s the equivalent of the emissions from powering more than 1.5 million UK homes for one year. So how can telco operators turn the tide?
Find the right fit for every job – it’s called dynamic resource allocation
Enter AI-enabled dynamic resource allocation. With assistance from AI algorithms, telecom operators can take an AI-powered network management approach to analyse real-time data such as traffic, technician availability, technician skill sets, and service history to ensure the right technician, with the right skills and parts, are 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.
Spot the signs before they happen
Telecom operators manage thousands of expensive assets, from fibre cables to cell towers and edge devices, 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% more than they need to on asset management. This struggle to assess the health and lifespan of assets leads to premature replacements or expected failures.
So many telco companies are left on the back foot because their traditional monitoring processes can’t predict potential outages, which has meant network failures are often detected after they impact customers—and the cost is high. For instance, UK businesses lost more than 50 million hours in internet downtime in 2023, which resulted in over £3.7 billion in losses. So, what can be done to pre-empt asset failure?
Make smart decisions at every stage of the asset lifecycle – it’s called predictive analytics
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 into failures. These insights are key to help operators decide when to maintain, refurbish, or retire assets.
For instance, rather than replacing assets on fixed schedules, an AI-powered network management approachallows for condition-based and usage-based maintenance strategies, which means assets are only replaced when truly necessary.
This shift to just-in-time maintenance provides telecom companies with a chance to fix issues before the end user realises or is even impacted. Instead, companies can schedule asset maintenance at optimal times to ensure fewer service interruptions and enable smarter allocation of maintenance crews to the most at-risk assets—both key factors in helping to improve network reliability and increase customer trust.
Don’t leave field worker unsupported at their moment of need
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. This lack of access to up-to-date and accurate knowledge slows down issue resolution and can damage customer satisfaction. So how can telco operators do more to support their workers on the front line?
Let GenAI become the go-to knowledge base for learning and development
This is where Generative AI (GenAI) acts as a reliable knowledge base. GenAI 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. Whether a technician is on-site troubleshooting a network fault or a support agent is handling a customer escalation, GenAI can surface relevant insights, suggest fixes based on past work order records, and provide step-by-step guidance. This speeds up issue resolution across the board.
There’s also the training benefit as new workers can use GenAI 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 that is capable of handling complex issues with confidence.
Look beyond the hype with intelligent networks powered by Agentic AI
On top of the AI that will be used to intelligently monitor and power the network, there is also another type of AI that will greatly affect the telecom network. 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. These includes robotics, agentic systems, new user interfaces, evolving applications and platforms, AI-enabled devices and IoT. 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 considering how fast the development is going, it could be just around the corner. Imagine if AI agents both using and maintaining the telecom networks could communicate. That will be a completely different type of future telecom network.
Telcos in an AI world
The telecommunications industry stands at a pivotal moment with the future of AI. While the promise of 5G has failed to meet consumer expectations for revolutionary service, the integration of AI-powered network management presents an opportunity to drive new value. Telecom operators that leverage the power of AI will be able to optimise network resources, predict and prevent issues before they disrupt service, and offer more dynamic experiences to their customers. The future of telecom hinges on this digital transformation, where AI doesn’t just improve connectivity but turns 5G into a true catalyst for growth.
Markus Persson 