Interview
BMC Helix’s Hector Villena discusses telcos’ autonomous network ambitions and how AI agents are unlocking hands-off OSS
As customer expectations rise and switching communication service providers (CSPs) becomes easier than ever, telcos are under intense pressure to differentiate through exceptional service and smarter operations. That pressure is driving a shift toward AI-powered automation, resulting in smoother service for customers and greater efficiency within telco operations.
This shift is at the heart of BMC Helix’s ServiceOps, the company’s cloud-native platform for service management, operations, and automation. Launched back in 2020, the platform quickly proved popular, resulting in BMC Helix being spun off as a separate company earlier this year.
“The landscape is changing very quickly, and flexibility is everything,” explained Hector Villena, Area Vice President for Sales in BMC Helix’s Telco Go-To-Market. “That’s why we decided to rearchitect the whole platform from the ground up, with a SaaS first mindset, open architecture, AI driven and completely interconnected. This means our customers can deploy On Prem or SaaS with the same capabilities” explained Hector Villena.
BMC Helix’s goal is to combine the company’s two strengths: Service Management and Operations Management. Traditionally these two fields have been largely separated in the telco world, with data largely siloed off and unavailable for simple cross-analysis. With the AI powered tools from BMC Helix, however, data from both worlds can be combined, resulting in a higher level of automation and efficiency.
“The biggest CSPs that we deal with have hundreds of thousands of assets, from servers and storage to network devices. Managing all of that is highly complex. We help them to visualise those assets and quickly assess how the components are related to each other. We then add our AI-driven OSS capabilities, analysing data, monitoring events, and providing a better understanding of that environment,” said Villena. “When you combine the ticketing information from the network with the data coming from events, metrics, logs, telemetry, etc. and use the topology of the services as a common map to link them, you have something really powerful.”
Within the network itself, the benefits of these advanced AI tools are already being felt by customers. Using AI and advanced analytics to assess network data, networks can be made to better anticipate and prevent service disruption, improving uptime and avoiding network outages. When an incident does occur, the platform can also use AI to support with diagnostic tools, allowing issues to be identified more quickly and many of the responses automated.
“You have millions of tickets going through those platforms. We collect data about previous incidents, then apply AI to help deliver a resolution,” said Villena. “Some of those resolutions can be automated, but for those that can’t, it’s still providing a major boost in efficiency. It’s providing the data and instructions so a Level 1 technician can handle the issue much faster.”
A growing role for AI agents
AI agents – AI algorithms specifically designed to automate workflows through problem solving and decision-making without human intervention – are playing a major role in this digital transformation. Telcos are already beginning to deploy these agents to automate various customer journeys, helping provide support to staff in call centres or create bespoke packages for B2B customers.
But, to Villena, AI agents’ biggest strength could be their use for internal telco operations. BMC Helix has released 12 agentic AI agents, focussing on areas of telco operations that can provide the biggest gains in efficiency. The ‘Employee Navigator’ agent, for example, serves as the first layer of AI interacting with the user in the Helix platform and can handle simply administration tasks for employees.
But the true magic happens when these agents are part of the resolution process. “With HelixGPT a technician can ask an agent for a problem classification synopsis, a brief root cause summary with the contextual information (metrics, events, behaviour of the system, etc.) and actionable insights. Following that, the technician can ask the system to provide step-by-step recommendations to solve the issue. Or if the issue is so complex it requires the involvement of different subject matter experts, it will automatically create a Microsoft Teams group chat pulling in the right resolution engineers where all relevant stakeholders can ask questions to the agent (to get a full 360º on the situation, RCA, etc.) and can work with each other to solve the ticket. These are just few of the use cases that can be delivered by the BMC Helix platform,” said Villena. “It’s optimizing not only the Mean Time to Repair, as it brings the resolution to L1, but also reducing the overall cost per ticket.”
BMC Helix is planning to expand their roster of AI agents in the coming months to cover even more use cases, helping to empower telco workforces even further.
Is the ‘Dark NOC’ within reach?
With more and more AI agents within the telco network, just how far can CSPs take automation within the Network Operations Centre (NOC)?
The NOC serves as the nerve centre of the network, the physical location from which network activity is monitored and managed. Currently, most NOCs are highly manual, with network engineers overseeing data traffic and the status of the networks’ vast physical and digital assets.
As AI and automation becomes more sophisticated, however, the need for manual, human intervention in the network is decreasing. This naturally leads us to the concept of a ‘dark NOC,’ a fully autonomous NOC that leverages AI and machine learning to manage the network without the need for any human oversight at all. This, says Villena, is the end-goal for most CSPs.
“CSPs are trying to work smarter, and as a result, automating as many operations as they can. A consistent objective for many CSPs is to reach ‘zero touch’ operations, where the operator does not interact manually with the network at all. Network incidents come into this big AI brain and then get identified, triaged, root caused, and resolved automatically. That’s the aspiration of all CSPs.”
But just how far we on this journey towards fully automated NOCs?
“We’re still a long way from [the dark NOC]. But each part of the network will have a different level of automation, with some already being highly automated,” said Villena. “There’s a big difference between the level of autonomy CSPs have in their network functions and their wider IT architecture.”
“In terms of their IT architecture, most CSPs I talk to categorise themselves as between Level 0 and Level 1,” he added, referencing TM Forum’s framework of Autonomous Networks Levels, with Level 0 being fully manual and Level 5 being fully autonomous.
But rapid advances with AI and related technology means progress towards greater automation has been fast.
“Some CSPs are aiming to have 80% of network incidents automated by the end of 2026, and full autonomy by 2030. That’s a very aggressive timeline, but the aspiration is clearly there,” said Villena. “AI has really enabled that transformation. We’re seeing some incredible results in our platform which really show this could be achieved in the next years. The level of improvement is enormous.”
Part of this acceleration relates to the increasing convergence of IT and telco functions.
“As networks are becoming more virtualised and cloudified, the division between the CSP’s NOC and IT systems is becoming blurred,” said Villena. “Part of our ‘Operations of the future’ strategy is to unify workflows, data, and processes across IT and NOC domains. With this, we’ll be able to help our customers move from Level 0 and Level 1 to Level 4 autonomy very quickly.”
The building blocks for even greater autonomy
While for now achieving the dream of a Dark NOC remains tantalisingly out of reach, there is little denying that the convergence of telco systems and the introduction of more sophisticated AI is making rapid progress towards this goal. AI-driven platforms like BMC Helix are proving critical in bridging the gap between legacy complexity and autonomous efficiency, helping to deliver better experiences for consumers and major cost savings for operators.
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