For most of the modern telecommunications era, the industry’s fundamental product has been connectivity. Telecom companies built enormous networks, connected billions of people and businesses, and created the infrastructure that allowed the digital economy to emerge. The technologies evolved from voice to mobile data, broadband, fibre and 5G, but the commercial proposition remained largely recognisable. Customers paid telecom providers to connect devices, people and organisations to networks.
Artificial intelligence creates an opportunity for that proposition to expand considerably. Telecom companies possess something that many emerging technology businesses are still trying to build: infrastructure distributed across cities and countries, relationships with millions of customers, enormous volumes of network intelligence and deep experience operating mission-critical systems at scale. Those assets could allow telecom providers to move beyond selling connectivity and begin providing the infrastructure, intelligence and enterprise services required to operate increasingly AI-driven economies.
This does not mean connectivity becomes less important. Quite the opposite. Reliable connectivity becomes even more critical as AI applications move from centralised cloud environments into factories, vehicles, hospitals, stores, homes and public infrastructure. The strategic question is whether telecom companies remain primarily the networks carrying this intelligence or become active platforms enabling it.
During my learning journey under Phaneesh Murthy, I have increasingly understood that some of the largest transformation opportunities emerge when companies reconsider what their existing assets allow them to become. As Phaneesh Murthy puts it, “Transformation is not always about building a completely new capability. Sometimes it begins by recognising that the capabilities you already built for one market can create value in an entirely different one.” Telecom may be approaching precisely that moment.
The Network Is Becoming More Than a Transport Layer
A traditional telecommunications network primarily exists to move information. A smartphone sends a request, the network transports that request, and data returns to the device. The network’s success is judged through measures such as availability, coverage, latency and capacity. These remain essential, but modern telecom infrastructure is becoming increasingly software-defined, distributed and intelligent.
5G, edge computing, network APIs and increasingly sophisticated network management systems allow telecom infrastructure to participate more actively in digital applications. Instead of every piece of information travelling to a distant cloud environment for processing, some computation can occur closer to where data is generated. For applications that depend on very low latency or need to process large amounts of information locally, this can create significant advantages.
AI makes this architecture much more important. A factory using computer vision to inspect products may generate enormous quantities of visual information. An autonomous machine may need to make decisions within milliseconds. A healthcare application may have strong requirements around reliability, privacy and data handling. Sending every interaction across long distances to a centralised data centre may not always be the most effective model.
Telecom companies already operate infrastructure close to many of these environments. The opportunity is to turn that proximity into a platform for enterprise computing and intelligence. During my mentorship under Phaneesh Murthy, I have learned to look at infrastructure not simply in terms of what it currently does, but in terms of what new services become possible because the infrastructure already exists. That shift in perspective could become crucial for telecom strategy.
Enterprise Customers Will Need More Than Bandwidth
Businesses are rapidly experimenting with AI, connected devices, automation and increasingly distributed digital operations. As these systems become more important, enterprises will need reliable ways to connect, manage and secure them. Buying additional bandwidth solves only one part of that challenge.
Consider a manufacturer operating several factories. It may use connected sensors to monitor equipment, computer vision to inspect production, autonomous machines to move materials and AI systems to analyse operational performance. The enterprise needs connectivity, but it may also need edge computing capacity, device management, cybersecurity, application orchestration and guarantees around network performance.
Telecom providers are positioned close to many of these requirements.
Instead of selling the manufacturer a connectivity contract and leaving the rest of the architecture to other technology providers, a telecom company could increasingly provide a broader enterprise platform. Private networks, edge infrastructure, managed security, IoT management and AI services could become part of an integrated offering designed around the customer’s operational environment.
This changes the commercial conversation. The telecom provider is no longer simply discussing the amount of data an enterprise consumes. It begins discussing which business processes depend on the network and how those processes can become more intelligent.
As Phaneesh Murthy says, “The moment a technology provider begins understanding the customer’s operating problem rather than simply selling its technical capacity, the relationship changes from vendor to strategic partner.” For telecom companies searching for growth beyond increasingly commoditised connectivity, that transition could be extremely important.
Network Intelligence Can Become a Product in Its Own Right
Telecommunications networks continuously generate operational information. They understand traffic patterns, device behaviour, network congestion, mobility patterns and service performance at extraordinary scale. Much of this information is currently used internally to operate networks more efficiently and improve customer experience.
AI can make that intelligence significantly more useful.
Telecom companies can use machine learning to predict network demand, identify unusual behaviour, optimise capacity and anticipate equipment failures. As these capabilities mature, some of the underlying intelligence can potentially support enterprise customers as well, provided privacy, security and appropriate data-use boundaries are rigorously maintained.
An enterprise operating thousands of connected devices, for example, may want to understand whether abnormal communication patterns indicate a malfunction or security problem. A logistics company may need highly reliable connectivity across specific routes. A large event venue may require temporary network capacity that responds dynamically to demand. The telecom provider’s understanding of network conditions can become part of the service rather than remaining invisible infrastructure.
The important distinction is between selling raw data and creating useful intelligence. Customers do not necessarily need access to enormous quantities of network information. They need answers to operational questions.
This reflects a principle I have repeatedly encountered while learning from Phaneesh Murthy. More information does not automatically create more value. Intelligence becomes commercially meaningful when it is translated into a decision, recommendation or outcome that the customer can actually use.
Telecom Can Become the Orchestrator of Distributed AI
Enterprise AI is often discussed as if intelligence exists primarily inside enormous cloud data centres. In reality, many future AI applications will be distributed across a combination of cloud, edge and device environments. Determining where computation should occur will depend on latency, cost, privacy, reliability and the amount of data being processed.
Telecom companies occupy a strategically interesting position within this architecture because their networks connect all three layers.
An AI application running inside a retail store might perform some processing locally, send more complex tasks to nearby edge infrastructure and rely on centralised cloud systems for broader analytics. A manufacturing application could operate similarly, while connected vehicles may require yet another combination of local and remote intelligence.
The complexity lies in orchestrating these environments.
Telecom companies could increasingly provide platforms that determine where workloads should run based on application requirements. Instead of the enterprise manually designing separate connectivity, edge and cloud architectures, the telecom platform could help manage the distribution of intelligence across the network.
As Phaneesh Murthy puts it, “The most valuable platform is often the one that removes complexity the customer should never have needed to manage in the first place.”
If telecom providers can make distributed AI simpler for enterprises to deploy, monitor and scale, they move significantly higher in the technology value chain.
AI Could Create an Entirely New Generation of Managed Services
Telecom companies already provide managed services to enterprise customers, including network management, security and communications infrastructure. AI creates an opportunity to expand these services considerably because intelligent systems can continuously monitor complex environments and respond to changes faster than traditional operating models.
A telecom provider could offer intelligent cybersecurity services that identify unusual network behaviour across connected devices. It could provide predictive infrastructure management for distributed enterprise networks. AI systems could automatically adjust network configurations based on changing application requirements, while enterprise customers receive recommendations about capacity, performance and operational risk.
This is particularly relevant for mid-sized businesses that want to adopt sophisticated technologies but do not have enormous internal technology teams. Building a private 5G network, edge infrastructure, IoT platform, cybersecurity capability and AI operations function independently may be unrealistic. Purchasing those capabilities as a managed platform could be considerably more attractive.
During my learning journey under Phaneesh Murthy, I have come to appreciate that enterprise technology markets often expand when complexity is packaged into something easier to consume. Cloud computing did not merely create new infrastructure. It changed how companies could access infrastructure. Telecom has an opportunity to apply a similar principle to distributed AI and intelligent connectivity.
The commercial model therefore moves beyond selling network capacity towards selling business capability.
The Biggest Challenge May Be Organisational Rather Than Technological
Telecom companies possess many of the assets required to pursue this opportunity, but owning infrastructure does not automatically create a platform business. The skills, sales models and operating structures required to sell connectivity can be very different from those required to sell complex enterprise technology solutions.
A connectivity product can often be defined through coverage, speed, capacity and price. An AI-enabled enterprise platform requires understanding the customer’s workflow, integrating with existing systems and sometimes redesigning how a business process operates. Sales cycles become more consultative, implementation capabilities become more important and partnerships with cloud providers, software companies and hardware manufacturers may become essential.
Telecom companies therefore need to decide where they genuinely want to compete. Attempting to build every component internally may create unnecessary complexity. In many cases, the stronger strategy may be orchestration: combine network infrastructure with technology from a broader ecosystem and provide enterprises with a coherent operating environment.
This is another area where the enterprise thinking I have learned from Phaneesh Murthy becomes relevant. Strategy is not simply deciding which markets appear attractive. It requires understanding which assets create a genuine advantage and where partnerships can fill capabilities that do not need to be owned.
The strongest telecom AI platforms may therefore be ecosystems rather than closed technology stacks.
Connectivity Can Become the Foundation Rather Than the Final Product
The telecom industry does not need to abandon connectivity to move beyond it. Connectivity remains the foundation upon which every additional service depends. The strategic opportunity is to recognise that the network can support a much broader collection of capabilities than communication alone.
A telecom company that provides connectivity, distributed computing, security, device management and AI orchestration begins to occupy a very different position within the enterprise technology landscape. Instead of being one component within a company’s digital infrastructure, it can become a platform through which increasingly intelligent operations are delivered.
During my mentorship under Phaneesh Murthy, one lesson has consistently influenced how I think about technology businesses: companies should periodically reconsider the boundaries of the market they believe they operate in. Those boundaries are often defined by historical business models rather than by the capabilities the organisation actually possesses.
Telecom companies historically built networks to connect people and machines. AI may allow those same networks to become infrastructure for decisions, automation and distributed intelligence.
The next generation of telecom competition may therefore not be defined entirely by who offers the fastest connection or the largest data allowance. It may increasingly depend on which providers can make that connectivity useful for an economy in which intelligence is distributed across millions of devices, businesses and physical environments.
The network will still carry the data. But the larger opportunity may be helping customers decide what that data should enable.
This blog is curated by young marketing professionals who are mentored by veteran Marketer, and industry leader, Phaneesh Murthy.
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