AI Is Revolutionizing Network Operations for Service Providers

The adoption of artificial intelligence (AI) is accelerating across the telecoms industry, with 88% of fixed broadband service providers now investigating or trialing AI automation to enhance their fixed broadband services, according to new research from Incognito Software Systems and Omdia.

Key use cases such as network monitoring, predictive maintenance, and resource optimization are at the forefront, driving significant cost savings and improving customer experiences.

"AI is no longer just a buzzword, it's a critical enabler for service providers as they look to automate operational processes in an effort to establish more efficient, high-performing networks," said Gary Knee, CEO at Incognito. "By understanding how AI is driving tangible benefits today, service providers can better define their strategies, focus on the right areas of investment, and choose the right solution partners to accelerate their network journey."

Key findings from the report include:

Observability and diagnostics present the most significant opportunities for AI

Nearly half of service providers (45%) cite network monitoring and troubleshooting as their top AI use case, followed by network provisioning (30%) and resource optimization (28%).

Top benefits of AI in network operations

Top benefits of AI in network operations include improved customer experiences and operational cost savings are the primary advantages expected by service providers.

Key KPIs for AIOps

When building business cases for AI, service providers are focused on customer experience metrics (e.g., reduced complaints, faster call handling, fewer truck rolls), network reliability (e.g., downtime costs, mean-time-to-repair), and operational efficiency (e.g., reduced errors, faster processes).

Partners are key for AI success

Service providers are relying on technology and OSS partners for AI projects, seeking guidance from vendors with proven solutions and industry expertise to develop effective implementations.

Methodology: The report is based on a global survey of service provider representatives and interviews with senior technology executives across Latin America, North America, Europe, and East Asia.

Hot Topics

The Latest

Redis Monitoring 101: Key Metrics You Need to Watch

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Beyond Traditional Autoscaling: The Future of Kubernetes in AI Infrastructure

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI Drives Surge in Data Budgets

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned Architecture Causes Service Disruptions, High Operational Costs and Security Challenges

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

How GenAI Can Save Time for the NetOps Team

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

Will AI Solve the Growing Data Divide?

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

Top Concerns for Tech Decision Makers

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

Gartner: Top Trends Shaping the Future of Cloud

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

The Great SaaS Hangover (and the Cure Nobody Is Talking About)

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

OpenShift Monitoring: 5 Things You Need to Keep an Eye on

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

AI Is Revolutionizing Network Operations for Service Providers

The adoption of artificial intelligence (AI) is accelerating across the telecoms industry, with 88% of fixed broadband service providers now investigating or trialing AI automation to enhance their fixed broadband services, according to new research from Incognito Software Systems and Omdia.

Key use cases such as network monitoring, predictive maintenance, and resource optimization are at the forefront, driving significant cost savings and improving customer experiences.

"AI is no longer just a buzzword, it's a critical enabler for service providers as they look to automate operational processes in an effort to establish more efficient, high-performing networks," said Gary Knee, CEO at Incognito. "By understanding how AI is driving tangible benefits today, service providers can better define their strategies, focus on the right areas of investment, and choose the right solution partners to accelerate their network journey."

Key findings from the report include:

Observability and diagnostics present the most significant opportunities for AI

Nearly half of service providers (45%) cite network monitoring and troubleshooting as their top AI use case, followed by network provisioning (30%) and resource optimization (28%).

Top benefits of AI in network operations

Top benefits of AI in network operations include improved customer experiences and operational cost savings are the primary advantages expected by service providers.

Key KPIs for AIOps

When building business cases for AI, service providers are focused on customer experience metrics (e.g., reduced complaints, faster call handling, fewer truck rolls), network reliability (e.g., downtime costs, mean-time-to-repair), and operational efficiency (e.g., reduced errors, faster processes).

Partners are key for AI success

Service providers are relying on technology and OSS partners for AI projects, seeking guidance from vendors with proven solutions and industry expertise to develop effective implementations.

Methodology: The report is based on a global survey of service provider representatives and interviews with senior technology executives across Latin America, North America, Europe, and East Asia.

Hot Topics

The Latest

Redis Monitoring 101: Key Metrics You Need to Watch

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Beyond Traditional Autoscaling: The Future of Kubernetes in AI Infrastructure

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI Drives Surge in Data Budgets

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned Architecture Causes Service Disruptions, High Operational Costs and Security Challenges

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

How GenAI Can Save Time for the NetOps Team

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

Will AI Solve the Growing Data Divide?

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

Top Concerns for Tech Decision Makers

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

Gartner: Top Trends Shaping the Future of Cloud

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

The Great SaaS Hangover (and the Cure Nobody Is Talking About)

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

OpenShift Monitoring: 5 Things You Need to Keep an Eye on

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...