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Bridging the Visibility Gap: A Path to Smarter Telecom Infrastructure

Jeff Collins
WanAware

Telecommunications is expanding at an unprecedented pace. With more than $300 billion invested in infrastructure since 2018, the industry is laying the groundwork for a new era powered by 5G, edge computing, AI-driven services, and smarter connectivity for everything from smart cities to remote healthcare. But progress brings complexity.

As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time.

The survey of 180 telecom leaders shows there's significant opportunity to enhance visibility across increasingly distributed, dynamic networks. While challenges persist, the data paints a clear path forward: intelligent observability is beneficial and foundational to unlocking the full return on infrastructure investments.

Investment Momentum Is Strong, But Oversight Must Keep Pace

The telecom sector is clearly in expansion mode. Over half (54%) of telecom leaders say their CapEx has increased over the past two years. Yet when it comes to investing in observability — the ability to monitor and act on network performance in real time — only 11% allocate more than 20% of their infrastructure budgets to it. This isn't due to a lack of interest. Rather, many leaders are navigating competing priorities. From expanding into rural markets to deploying new services and meeting customer demands, observability tools can sometimes fall behind in the investment queue.

Still, the connection is clear: visibility enables agility. Just 7% of respondents report having near-complete insight into their infrastructure today, while 62% say they can see less than half of their assets. Closing that gap isn't just about better monitoring. It's about maximizing the potential of every other initiative, from automation to sustainability.

Shared Infrastructure Is a Strategic Asset With New Visibility Requirements

The future of telecom lies in collaboration. Network-to-network interfaces (NNIs), which allow providers to share infrastructure and extend service reach, are now commonplace. Nearly 70% of respondents participate in at least one such arrangement, with some engaged in more than 10. These partnerships unlock powerful capabilities, but also introduce new layers of complexity. The survey found that 55% of operators have experienced service disruptions that could have been avoided with greater visibility, especially across shared or third-party infrastructure.

The good news? This is a solvable challenge. The more providers embrace observability as a shared priority — not just an internal one — the more resilient and high-performing these partnerships can become.

AI's Potential Is Real, But It Needs a Clear Line of Sight

There's widespread excitement about AI's role in telecom. From predictive maintenance to real-time anomaly detection, AI has the power to radically improve network operations. And adoption is growing: 57% of telecom leaders say they're piloting or beginning to implement AI-powered observability tools. Yet only 7% have fully deployed these solutions, and only 6% have seen a dramatic improvement in downtime.

What's holding things back? Respondents pointed to budget constraints, legacy system compatibility, and a need for specialized talent. But the biggest factor may be foundational visibility. AI is most effective when it operates on real-time, accurate data from across the network. AI can't optimize what it can't see. The solution lies in making observability a core component of AI strategies, not an afterthought.

Expansion Brings New Opportunities and Responsibilities

As the industry pushes to close the digital divide, providers are extending fiber, building towers, and deploying edge technologies in regions that have long lacked connectivity. These expansions are essential for equity and economic growth. At the same time, they present a new set of challenges. Roughly 40% of telecom leaders report that over a quarter of their network is currently insufficiently monitored, and one in four say they're not confident in their visibility into recently expanded areas.

Tool complexity is part of the issue. 30% of respondents use seven or more different tools to monitor their networks, making it harder to achieve a unified view. Simplifying and integrating observability can help providers stay ahead of operational demands, especially as networks become more decentralized.

Readiness for the Future Starts with Visibility Today

Telecom leaders are investing in next-generation architectures — from XaaS models to edge services — but many acknowledge they're not yet fully prepared to support these innovations with current visibility tools. Only 27% say they feel ready to provide observability for AI-intensive applications, and 80% report that their monitoring is still mostly manual.

Still, optimism is high. The majority of respondents recognize the need for change, and many are actively working to modernize their observability approach. As the industry continues to evolve, there's a clear appetite for solutions that are intelligent, integrated, and built to scale.

Building a Smarter, More Resilient Future

Observability is no longer optional. It's the key that unlocks everything else. When providers can see their networks clearly, they're better equipped to deliver reliable service, reduce downtime, detect threats early, and respond with speed and confidence. The good news from this year's benchmark report is that telecom leaders are asking the right questions, and many are taking steps toward better visibility. With the right tools and strategies, the industry has the opportunity to close the visibility gap and usher in a new era of efficient, AI-powered operations. As we continue building the networks of the future, observability will be the foundation we build on.

Jeff Collins is CEO of WanAware

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

Bridging the Visibility Gap: A Path to Smarter Telecom Infrastructure

Jeff Collins
WanAware

Telecommunications is expanding at an unprecedented pace. With more than $300 billion invested in infrastructure since 2018, the industry is laying the groundwork for a new era powered by 5G, edge computing, AI-driven services, and smarter connectivity for everything from smart cities to remote healthcare. But progress brings complexity.

As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time.

The survey of 180 telecom leaders shows there's significant opportunity to enhance visibility across increasingly distributed, dynamic networks. While challenges persist, the data paints a clear path forward: intelligent observability is beneficial and foundational to unlocking the full return on infrastructure investments.

Investment Momentum Is Strong, But Oversight Must Keep Pace

The telecom sector is clearly in expansion mode. Over half (54%) of telecom leaders say their CapEx has increased over the past two years. Yet when it comes to investing in observability — the ability to monitor and act on network performance in real time — only 11% allocate more than 20% of their infrastructure budgets to it. This isn't due to a lack of interest. Rather, many leaders are navigating competing priorities. From expanding into rural markets to deploying new services and meeting customer demands, observability tools can sometimes fall behind in the investment queue.

Still, the connection is clear: visibility enables agility. Just 7% of respondents report having near-complete insight into their infrastructure today, while 62% say they can see less than half of their assets. Closing that gap isn't just about better monitoring. It's about maximizing the potential of every other initiative, from automation to sustainability.

Shared Infrastructure Is a Strategic Asset With New Visibility Requirements

The future of telecom lies in collaboration. Network-to-network interfaces (NNIs), which allow providers to share infrastructure and extend service reach, are now commonplace. Nearly 70% of respondents participate in at least one such arrangement, with some engaged in more than 10. These partnerships unlock powerful capabilities, but also introduce new layers of complexity. The survey found that 55% of operators have experienced service disruptions that could have been avoided with greater visibility, especially across shared or third-party infrastructure.

The good news? This is a solvable challenge. The more providers embrace observability as a shared priority — not just an internal one — the more resilient and high-performing these partnerships can become.

AI's Potential Is Real, But It Needs a Clear Line of Sight

There's widespread excitement about AI's role in telecom. From predictive maintenance to real-time anomaly detection, AI has the power to radically improve network operations. And adoption is growing: 57% of telecom leaders say they're piloting or beginning to implement AI-powered observability tools. Yet only 7% have fully deployed these solutions, and only 6% have seen a dramatic improvement in downtime.

What's holding things back? Respondents pointed to budget constraints, legacy system compatibility, and a need for specialized talent. But the biggest factor may be foundational visibility. AI is most effective when it operates on real-time, accurate data from across the network. AI can't optimize what it can't see. The solution lies in making observability a core component of AI strategies, not an afterthought.

Expansion Brings New Opportunities and Responsibilities

As the industry pushes to close the digital divide, providers are extending fiber, building towers, and deploying edge technologies in regions that have long lacked connectivity. These expansions are essential for equity and economic growth. At the same time, they present a new set of challenges. Roughly 40% of telecom leaders report that over a quarter of their network is currently insufficiently monitored, and one in four say they're not confident in their visibility into recently expanded areas.

Tool complexity is part of the issue. 30% of respondents use seven or more different tools to monitor their networks, making it harder to achieve a unified view. Simplifying and integrating observability can help providers stay ahead of operational demands, especially as networks become more decentralized.

Readiness for the Future Starts with Visibility Today

Telecom leaders are investing in next-generation architectures — from XaaS models to edge services — but many acknowledge they're not yet fully prepared to support these innovations with current visibility tools. Only 27% say they feel ready to provide observability for AI-intensive applications, and 80% report that their monitoring is still mostly manual.

Still, optimism is high. The majority of respondents recognize the need for change, and many are actively working to modernize their observability approach. As the industry continues to evolve, there's a clear appetite for solutions that are intelligent, integrated, and built to scale.

Building a Smarter, More Resilient Future

Observability is no longer optional. It's the key that unlocks everything else. When providers can see their networks clearly, they're better equipped to deliver reliable service, reduce downtime, detect threats early, and respond with speed and confidence. The good news from this year's benchmark report is that telecom leaders are asking the right questions, and many are taking steps toward better visibility. With the right tools and strategies, the industry has the opportunity to close the visibility gap and usher in a new era of efficient, AI-powered operations. As we continue building the networks of the future, observability will be the foundation we build on.

Jeff Collins is CEO of WanAware

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.