Yogesh Malik, New Tech Investor / Global CTIO / CTO & CIO of the Year 2017 / Customer / Data Flows.
In the modern telecommunications landscape, the promise of artificial intelligence (AI) looms large. Yet, for many telecom companies, the road to AI adoption remains painfully slow. The issue isn’t just about technology readiness or infrastructure—it’s business-related, structural. The way telecoms are organized creates a widening gap between key decision makers and the levers of AI transformation: data, domain knowledge and operational layers.
Each telecom company is unique, but they all operate in standardized industries. Yet, most still lack proper documentation of internal processes. Knowledge stays trapped within people and departments, not systems. The value chain is fragmented by churn, and expertise is locked in silos, preventing it from being used for growth. Meanwhile, management rarely acts as technical contributors, creating a cultural gap between leadership and technology. This combination makes telecoms risk-averse and slow to translate innovation into action. Without embracing new technologies, telecoms will remain commodity suppliers and keep missing out on opportunities to lead the digital data-driven future.
The Layers Of Distance
Imagine the telecom organization as various layers on top of each other. Management, the top layer, is often strategic and visionary, but increasingly removed from innovation which is enabled by the technology layer. Beneath that is the business process layer, where decisions about efficiency and process optimization are made. Then comes the data layer, where the real power lies. At the foundation, infrastructure provides networks that make it all possible.
This hierarchy, while efficient for traditional telecom operations, has become an obstacle for transformation. Many CEOs are several layers removed from the data that could inform next-generation business models. The result is a strategic vision that lacks the understanding required to make AI more than a trend.
Data: The Untapped Goldmine
Telecom data is uniquely rich, spanning customer behavior, mobility, consumption and preferences across geographies and lifestyles. Mobilizing and understanding these vast amounts of data requires infrastructure agility and deep knowledge. Data scientists and AI engineers can build applications and data processing models, but without business context, the output regularly falls short of strategic value. Additionally, while high-level executives understand the market, they can’t directly touch the data or the tools that analyze it. Or they are not sure how. Dependent on the organization below them, they are not able to make change happen. The process is too lengthy and complex, and technology runs fast.
This divide is where competitors are pulling ahead. Take Meta as an example. The company is designing new data architecture closely linked to AI and with embedded decision-making throughout the process. That proximity between knowledgeable top leadership, data and AI capability is exactly why Meta and similar tech companies are successful. If telecoms learned from tech companies and applied a similar all-encompassing approach, they could tap into a true opportunity.
The Generation And Relevance Gap
There’s also a generational divide at play. Many telecom leaders emerged from eras focused on essential utility, where reliability, coverage and regulatory compliance were the Holy Grail. But the modern value stack is shifting. Foundational is the essential utility layer (connectivity as a given, a commodity). Above that are arbitration layers where ad hoc services shape daily user engagement. At the top is entertainment, where competition and data usage peak.
Ironically, telecoms provide the backbone for these experiences, yet rarely participate in the value creation occurring on top of them. AI thrives in those upper layers where personalization, prediction, engagement and customer behavior are taking the lead. If telecoms remain stuck optimizing the bottom layers, they’ll continue to be infrastructure providers for someone else’s intelligence and gain.
Future-forward telecoms must flatten their layers. Management teams need direct visibility into data-driven decision-making. Chief information officers and chief technology officers should be at the heart of the business, not in a technical corner room. Knowledge of the details of how data is generated, processed and translated into customer insight will determine success.
Telecoms need to move from being passive enablers to active participants in the digital future. That starts with leadership understanding not just the potential of AI, but having the trust to adopt the structure that keeps it close to them.
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