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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

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

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

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...