- February 2026
For today’s telecommunications companies, industrial 5G services promise to deliver not only sustainable growth and new revenue streams, but also an opportunity to successfully reframe their role in a rapidly evolving industry. In this risk-averse space, where resilience and compliance are non-negotiable, telcos are ideally placed to outmaneuver newer entrants, including the hyperscalers determined to own these valuable enterprise relationships themselves.
However, telcos still need to convince industrial clients such as airports, distribution centres, and manufacturing plants that the rewards of 5G deployments outweigh the risks. Success depends on effectively mitigating clients’ migration concerns, while translating 5G’s technological advantages into demonstrable business benefits.
This is where AI can make all the difference.
Adding value with cognitive digital twins
In this new era of highly complex 5G networks, the cognitive digital twin is emerging as a keystone technology.
Like traditional digital twins, cognitive digital twins present a real-time, virtual model of network operations. Unlike traditional digital twins, they’re able to autonomously test and learn, improving accuracy over time, and taking actions to improve network efficiency, performance, and resilience.
Telcos can also use cognitive digital twins to broaden their industrial 5G offering, and compete with hyperscalers at the industrial platform layer. Instead of selling 5G connectivity and commodity IoT SIMs, telcos can position fully featured Network-as-a-Service solutions backed by cognitive digital twins. For industrial clients, a digital twin that includes both connectivity and infrastructure layers (and can autonomously simulate complex network failure and reconfiguration scenarios) should prove a compelling proposition.
AT&T is already using AI-powered simulation to improve network resilience. The AT&T Geo Modeler1 is a Generative AI system that uses synthetic data and a Network Foundation Model to simulate and predict network coverage under dynamically changing network and environmental conditions.
O2 Telefónica, meanwhile, has developed a digital twin to map every component of the O2 network. The highly automated model is transforming capacity planning, and has reduced the number of mobile communications sites with temporary bottlenecks by 90%2.
Strengthening the proposition with zero-touch operations
Many telcos see cognitive digital twins as a stepping stone towards an even more valuable destination: highly autonomous, self-healing networks.
Telcos know that managing and optimizing increasingly complex 5G networks, in real time, is beyond the scope of traditional, rules-based automation. Many are already working on Level 4 autonomous networks3 that use agentic AI and cognitive orchestration to handle complex, cross-domain operations, predict issues, and self-heal.
Again, for the telcos that win this race, improved network performance and resilience won’t be the only rewards. They’ll also be able to make a more compelling case for industrial 5G.
Compared with the legacy network infrastructure of industrial clients, 5G already promises a step change in terms of network flexibility and quality of service. Once telcos successfully integrate 5G’s technological superiority with cognitive orchestration, the proposition will be even harder to ignore: zero-touch network operations backed by unprecedented SLAs.
The smartest telcos will sell the business impact of autonomous 5G networks as clearly as their performance and resilience advantages. A production line in a smart factory, for example, will be able to hit new heights of efficiency with AI proactively identifying and fixing network latency and other connectivity issues.
Some telcos have already demonstrated significant progress on cognitive orchestration. Deutsche Telekom’s RAN Guardian Agent, for example, works alongside other AI applications to identify network irregularities and autonomously takes corrective actions to optimize performance. The AI has helped to cut troubleshooting times from hours to minutes.4
Other telcos must follow suit or risk falling behind their peers. BearingPoint research shows the use of AI in self-organizing networks is projected to grow from 13% to 30%5 in the next three years, as manual operations cease to be a focus.
Augmenting skills as a transformation partner
Telcos can also strengthen and differentiate their industrial 5G offerings through the development and provision of specialized GenAI copilots.
Industrial copilots with natural language interfaces can empower business users and augment the skills of technicians, dramatically boosting technician efficiency and reducing mean time to repair. Vodafone, for instance, is using GenAI-powered natural language queries6 to help non-technical staff generate SQL queries and accelerate document search during root cause analysis.
Just as with cognitive digital twins and autonomous networks, the internal efficiency such copilots promise to unlock is only half the story. Telcos that build industrial copilots into their industrial 5G offerings stand to strengthen their position as a key partner in strategic transformation.
Telcos need to rapidly converge their 5G and AI roadmaps
To seize this opportunity – accelerating the shift to industrial 5G, and broadening their business to compete with hyperscalers – telcos will need to be much bolder on AI adoption. They must think beyond isolated PoCs and experimental AI pilots, and develop a converged AI and 5G roadmap. Telcos should focus their efforts on the following high-impact areas:
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Automating predictive maintenance and dynamic resource allocation
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Optimizing network performance in real time with AI-powered analytics
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Embedding AI into core operational workflows
Accelerating AI-driven transformation in telecommunications network operations requires a strategic balance of technology adoption and organizational alignment.
Success also depends on enabling cross-functional collaboration, upskilling teams, and ensuring initiatives progress beyond pilots to deliver measurable efficiency gains and enhanced customer experience at scale.
A recent BearingPoint study7 of 1,000 C-level executives reveals that scaling AI remains a challenge:
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8%
achieved the scale initially envisioned in their business cases.
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68%
cite cross-functional collaboration as the key best practice for scaling AI across the organization. Importantly, scalability is not just a technical issue.
A converged AI and 5G roadmap can provide a crucial focal point for telcos. As part of a broader transformation strategy, it can drive and guide collaboration in a host of key areas, from use case prioritization to AI skills development.
With functions and operational teams pulling in the same direction, telcos will be able to set ambitious timelines for achieving AI-driven performance and efficiency gains, and translating them into stronger industrial 5G offerings and client experiences.
Ultimately, developing AI alongside 5G as part of a single strategic roadmap will move the needle on the challenges that keep telco leaders awake at night: automating operations to safeguard margins, opening doors further up the value chain, and stabilizing the business, while reframing it to thrive in years to come.
Telecommunication companies must act fast to turn industrial 5G into both a critical source of growth, and a powerful catalyst for strategic transformation.
[1] AT&T, AT&T Geo Modeler™: Enhancing Network Optimization & Planning with AI, October 2025
[2] Telefónica, Digital twin puts O2 mobile network on autopilot, October 2025
[3] TM Forum, Autonomous networks: Level 4 industry blueprint, June 2024
[4] Deutsche Telekom, Deutsche Telekom: AI agents for mobile network, November 2025
[5] BearingPoint, Resilient by design: how agentic AI is reinventing organizations, September 2025
[6] Google, How Vodafone is using gen AI to enhance network life cycle, November 2024
[7] BearingPoint, Resilient by design: how agentic AI is reinventing organizations, September 2025
