Research says 48% of operators are scaling AI beyond pilots but the biggest barriers are structural – 62% identify data quality and integration issues and 47% cite lack of scalable infra
The conversation around autonomous networks and AI-native telcos has reached new heights, as major players continue to turn to the technology to manage operations. The ambition to be AI-empowered is evident, and by strengthening foundational capabilities, operators can unlock the full potential of intelligent, automated networks.
AI is genuinely transforming how networks are run, how customers are served, and how operators think about future growth. However, realising its full potential requires infrastructure that can absorb and sustain the technology’s significant computational demands. For telcos, this creates a clear strategic imperative and a compelling commercial opportunity. Those who invest in modernising their core infrastructure now will be best placed to scale AI effectively, efficiently, and to a lasting advantage.
The central question for telcos today is not whether to pursue AI. The question is one of sequencing and strategy. Operators who build strong infrastructure foundations alongside their AI ambitions will find AI a powerful accelerant, delivering returns not only in operational efficiency, but in service quality, customer trust, and long-term competitiveness.
Trust is built on fundamentals, not features
For telcos’ customers, reliability remains the ultimate benchmark. It is measured in access, consistency, and cost. When service is disrupted, the impact on customers’ trust and brand reputation is both immediate and significant. Operators are expected to innovate while ensuring the uninterrupted connectivity that users depend on in this digital age.
Operators that invest in stronger infrastructure are better placed to manage costs effectively, explore new revenue opportunities, and build the operational case for sustained investment in future capabilities.
A recent report from Tata Consultancy Services on the state of AI in telecoms reflects this. AI adoption is moving from pilot to scale, with 48% of telecom operators now scaling AI deployments beyond pilot stages. But despite strong momentum, the biggest barriers are structural: 62% identify data quality and integration issues and 47% cite lack of scalable infrastructure.
This highlights that AI is not limited by the technology itself. Rather, progress depends on how ready the underlying environment is to support and sustain it.
The strategic foundation for AI at scale
Instead of chasing the latest trend, operators must prioritise modernising core systems, stabilising their data environments, and strengthening observability across the network, providing a more effective route to resilience and stability.
This is especially true where infrastructure has become obsolete. If critical systems cannot be patched, monitored, or integrated properly, the risk of failure rises sharply. In that situation, AI cannot provide a complete solution. It can help surface issues earlier, but addressing underlying technical debt is essential to strengthening long-term stability.
That is why the most effective AI strategies in telecoms are not “AI-first” in the abstract. They are infrastructure-first, with AI used selectively to improve predictability, accelerate testing, reduce downtime, and support operational decisions. The goal is not to automate fragility but to reduce it.
From data overload to operational intelligence
The opportunity AI presents for telco resilience is substantial. Networks generate enormous volumes of operational data such as call records, performance metrics, and usage patterns. AI enables operators to process that information at speed, detect anomalies, identify patterns, and surface early indicators of potential service issues before they develop into disruptions.
According to that same TCS report, this is already where telcos are directing investment. 81% are using AI to strengthen networks and operations, closely followed by customer experience, with 73% citing modernising legacy systems as the key focus for AI use. This signals a clear and encouraging shift in the industry: from experimentation towards practical applications that deliver measurable improvements in reliability and service assurance.
The next stage of this evolution will be shaped by the quality of the underlying environment. AI-driven operations perform best with clean data, interoperable systems, robust governance, and infrastructure capable of supporting real-time decisions. Legacy modernisation is therefore not simply a technical undertaking. It is the foundation upon which stronger customer outcomes are built.
Modern infrastructure unlocks AI’s true value
When telcos invest in modernisation, the benefits extend well beyond IT efficiency. They create the conditions needed for improved service delivery, more consistent performance, and stronger customer relationships.
A modern network architecture supports more effective demand management, faster incident recovery, and the confident introduction of new digital services. Stronger system integration improves visibility across the customer journey, reducing friction in everything from provisioning to support.
Higher quality data enables more personalised, responsive, and accurate customer interactions. And a well-maintained, resilient infrastructure provides the foundation from which operators can innovate with greater confidence.
This is where AI can have its most lasting effect. Not as an add-on layered over an old model, but as an intelligent enabler of a better operating foundation. Used in this way, AI supports human teams, improves service predictability, and helps telcos build stronger, more trusted relationships with customers.
That is especially important at a time when industry expectations are rising, and coverage remains a core economic issue. Mobile coverage is not just a consumer issue; it is an economic one. Reliable networks underpin business productivity, digital services, and everyday connectivity. In that context, customer engagement is won through consistency, not novelty.
Laying the groundwork for lasting AI advantage
Well-integrated systems and properly maintained infrastructure are not simply prerequisites for AI: they are the conditions that determine how much value it can generate. Operators who address these early, whether by modernising legacy systems, strengthening data pipelines, or improving network observability, create the platform from which AI can perform at its most effective.
The path forward is clear. Telcos that invest in their foundations today will find themselves better equipped to absorb, scale, and lead with AI as the technology continues to mature. In an industry where the next generation of network capability, from autonomous operations to AI-native service delivery, is approaching rapidly, the operators that modernise now will be best positioned to scale their AI capabilities from a position of genuine strength.
From there, the rewards are clear: stronger customer relationships, greater operational efficiency, and a platform for AI-driven growth that compounds in value as the technology continues to advance.
About the author (pictured)
Akhilesh Tiwari is President, Communications, Media and Information Services (CMI) at Tata Consultancy Services (TCS)
