How AI is reshaping telecom carrier operations
Automation driven by artificial intelligence is sparking a deep transformation in the telecom industry. Telecom networks have gotten so complex in recent years that keeping everything running manually just doesn’t make sense anymore. At the same time, customers want stable connections, fast support, and zero hassle. This scenario puts carriers in front of an unavoidable challenge: modernize end to end without sending costs through the roof.
That was exactly the focal point Sutherland brought to MWC Barcelona 2026, widely regarded as one of the biggest global events in the telecom industry. In a conversation with The Fast Mode, Jay Naillon, VP and Global Solutions Leader for Telecom, Media, Technology, and Utilities at the company, explained how AI-agent-based operations are enabling carriers to ditch reactive, manual models in favor of autonomous, predictive systems. In practice, this means less operational effort, fewer service outages, and a significantly better customer experience — with issues resolved before the user even realizes something was wrong. 🚀
What really stands out about this shift is that we are not talking about promises five years down the road. Automation powered by AI is already in production at major carriers and delivering measurable results. According to Naillon, Sutherland’s agentic approach involves artificial intelligence agents that can make decisions autonomously within complex operational workflows, such as network provisioning, fault resolution, and customer service. These agents continuously learn from telecom network data and begin to anticipate problematic scenarios, acting proactively instead of waiting for a complaint to hit the call center.
The part of the value chain under the most pressure to reinvent itself
When asked which part of the telecom value chain is facing the greatest pressure for reinvention, Jay Naillon was straightforward: network operations and automation. According to him, the industry urgently needs to move past traditional, reactive models and embrace AI-first autonomous systems. At MWC 2026, Sutherland’s focus was on what they call agentic operations, where closed-loop intelligence, predictive analytics, and multi-agent orchestration redefine how networks operate day to day.
This reinvention is not a tech vanity project — it is a concrete necessity. Communication service providers face a combination of factors that make transformation impossible to postpone: growing network complexity, ever-rising customer expectations for real-time performance, and constant pressure to cut service costs. Naillon explained that carriers need to migrate from manual, siloed processes to intent-driven autonomous operations. This type of approach reduces OpEx, improves MTTR (mean time to repair), and elevates the customer experience across every layer of infrastructure, including RAN, core, transport, private networks, and customer service channels.
For Naillon, this transformation combining artificial intelligence, automation, and engineering expertise is critical for long-term resilience and competitive differentiation among carriers. Those who don’t make this transition now risk falling behind in an increasingly demanding and fast-moving market.
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Operational efficiency in practice, not just on paper
One of the most relevant aspects of this transformation is the real gain in operational efficiency. Historically, carriers rely on massive teams to monitor networks, handle incidents, and respond to customer tickets. With AI agents stepping into these processes, a significant chunk of this repetitive, manual work gets absorbed by automation. Naillon highlighted that with Sutherland’s agentic automation models, it is possible to achieve a 30% to 40% reduction in manual operational effort, freeing up human teams to focus on strategic, higher-value tasks.
This is not about replacing people — it is about reallocating talent to where it truly makes a difference, while AI handles what is predictable and scalable. Incident detection and resolution becomes faster, MTTR improves significantly through predictive analytics and closed-loop remediation, and network availability increases across RAN, core, and transport environments.
On top of that, operational efficiency takes on another dimension when we talk about predictive maintenance in telecom networks. Instead of waiting for equipment to fail before dispatching a field crew, artificial intelligence systems analyze network behavior patterns and identify anomalies before they turn into problems visible to the end user. This drastically reduces downtime and the cost of corrective maintenance, which tends to be far more expensive than acting preventively. For carriers, this kind of approach completely changes the financial equation of network operations.
Another point worth highlighting is the ability to scale these solutions. Unlike traditional automation projects that often stay confined to a single department or specific process, the agentic approach allows the same AI agents to be replicated and adapted for different contexts within the carrier. An agent trained to solve connectivity issues on fixed networks, for example, can be adapted to work on mobile networks or customer service workflows. This flexibility is essential for carriers that need to juggle multiple network technologies simultaneously, including 4G, 5G, and fiber optics.
Concrete results within one to two years after deployment
One of the most important questions posed to Naillon during the MWC 2026 interview was about the concrete results carriers can expect after adopting Sutherland’s solutions. The answer was pretty straightforward: within one to two years of deployment, carriers can expect measurable improvements in efficiency, resilience, and customer experience.
Sutherland’s agentic automation models enable:
- 30% to 40% reduction in manual operational effort
- Faster incident detection and resolution
- Significant improvement in MTTR through predictive analytics and closed-loop remediation
- OpEx reduction and better SLA adherence
- Higher network availability across RAN, core, and transport environments
But the gains go beyond operations. Intelligent automation also improves customer satisfaction by minimizing service disruptions and speeding up problem resolution. Naillon made a point of emphasizing that these results are measured through clear indicators: automation rates, incident reduction, MTTR improvement, cost-to-serve metrics, SLA performance, and NPS impact. In other words, this is not guesswork — it is hard data that proves business value and supports lasting competitive advantage.
The direct impact on customer experience
When we talk about customer experience in telecom, the traditional landscape is not exactly encouraging. Long hold times when calling support, generic responses that don’t actually solve the problem, and having to repeat information over and over are complaints pretty much everyone has had with a carrier at some point. Automation powered by artificial intelligence tackles exactly these pain points. AI agents can access the customer’s complete history, understand the context of the issue, and offer personalized solutions in real time, without that exhausting back-and-forth we all know too well.
Jay Naillon explained during the event that Sutherland has been working with carriers to implement support workflows where AI resolves the vast majority of first-level tickets in a fully autonomous way. When a problem requires human intervention, the artificial intelligence agent already hands the support rep the full prior diagnosis, interaction history, and even resolution suggestions. This means that even in the more complex cases, the customer experience improves because support becomes faster, more accurate, and less frustrating. Customers notice the difference, and it shows directly in metrics like NPS and churn rate.
There is also an indirect effect that often flies under the radar. When telecom networks run better thanks to predictive maintenance and intelligent automation, the volume of support tickets naturally drops. Fewer network problems mean fewer unhappy customers calling in to complain. This creates a positive cycle where operational efficiency feeds into better customer experience, which in turn eases the pressure on support teams. It is the kind of result that only shows up when technology is applied in an integrated way rather than in isolated silos.
The role of multi-agent orchestration
A concept that came through strongly in Sutherland’s presentation at MWC 2026 was multi-agent orchestration. In practice, it means there is no single AI agent handling everything. Instead, multiple specialized agents work together, each responsible for a piece of the process, communicating with one another to ensure end-to-end problem resolution happens without interruption.
Picture this: a customer complains about slow connection speeds. One AI agent analyzes network performance in that region, another checks whether there are open incidents that might be causing degradation, a third pulls up the customer’s history to see if it is a recurring issue, and a fourth agent kicks off an automatic remediation procedure. All of this happens in seconds, in a coordinated fashion, with no human intervention needed in most cases.
This multi-agent approach is what sets Sutherland’s offering apart from simpler automation solutions built on fixed rules. The AI agents don’t just follow a pre-programmed script — they interpret context, learn from past situations, and adapt their decisions based on the scenario they encounter. This is especially important in telecom, where the sheer diversity of equipment, technologies, and network configurations makes it nearly impossible to manually anticipate every possible scenario.
Intent-driven operations and the autonomous future
Another relevant concept Naillon brought up is intent-driven operations. The idea is that instead of programming each individual action the network should execute, the operator defines high-level objectives — like ensuring a certain level of availability or prioritizing video traffic during peak hours — and the artificial intelligence systems take care of translating those intentions into concrete actions and continuous network adjustments.
This model represents a considerable paradigm shift. Instead of engineers manually configuring hundreds of parameters, the network self-optimizes based on defined goals. It is an important step toward what the industry calls the autonomous network, where telecom infrastructure operates with minimal human intervention, dynamically adapting to traffic conditions, demand, and potential failures.
What to expect going forward
The movement Sutherland showcased at MWC Barcelona 2026 reflects a trend that is set to intensify over the coming years. As telecom networks become even denser with 5G expansion and 6G on the horizon, the reliance on intelligent automation will only grow. Carriers already investing in agentic artificial intelligence get a head start, both in operational efficiency and in the ability to deliver a customer experience that truly stands out in the market.
The combination of AI, automation, and engineering expertise that Sutherland presented is not just a response to current challenges — it is a bet on long-term resilience. In a market where the difference between retaining and losing customers can come down to how fast a problem gets resolved or how stable a connection stays, investing in autonomous operations is no longer optional.
The takeaway from the event is clear: the era of manual telecom operations is running out of time. Those who embrace this transformation now will reap the rewards in efficiency, cost reduction, and customer satisfaction. Those who wait risk competing at a disadvantage in a landscape where artificial intelligence is no longer a differentiator — it is table stakes. 📡
