105 pre-developed components with their own data and operational processes. “We can get customers a large part of the way there,” Lievano says. “They still need to connect it to their own systems, but the foundation is already in place.” For telecom operators looking to adopt similar approaches, data remains a critical consideration. “Agents are only as good as the data they have access to,” Lievano notes. In many organisations, data is still siloed and difficult to access, limiting the effectiveness of AI-driven systems. Addressing this requires a more unified approach to data management, ensuring that information from across the network can be accessed, understood and acted upon in a consistent way. Another key challenge is ensuring determinism in decision-making. While large language models are powerful, their outputs can vary depending on context, which is not acceptable in network operations. “You need consistent, repeatable outcomes,” Lievano explains. To achieve this, Microsoft combines AI reasoning with curated data, predefined workflows and validated queries, reducing variability and increasing trust in the system. “AI can leverage deterministic systems to enforce safety constraints, while routing irreversible actions to human operators, ensuring that ultimate control remains with people,” says Billor. Lievano adds: “Developing and refining these practices has been part of our journey, and we can now provide that guidance to our partners.” For operators, there is proven value in increasing the level of autonomy in their network. In its Scaling the AI-native telco report, McKinsey found that there was a 30 per cent reduction in network downtime from deploying AI for network management and maintenance, while Capgemeni reported in Networks with Intelligence 2024 that 71 per cent of telecom operators had reduced their energy consumption through autonomous network initiatives. As demand for connectivity continues to grow, the pressure on telecom operators to embrace these improvements in efficiency and resilience will only intensify. For Lievano, the case for change is inevitable. “Autonomous networks are a high priority for virtually every single operator because they spend so much money managing their network,” he says. “With the pace of growth today, the traditional approach of simply adding more engineers isn’t going to be sustainable.” The introduction of AI agents is not, therefore, simply a case of automation. They are redefining how work is organised, creating systems where humans and AI collaborate to deliver faster, more reliable and more intelligent networks that are prepared for the unprecedented demands on modern telecom operators. “When we first started this project, the models were about the level of a good engineering intern,” says Lievano. “Now they are essentially senior engineers, with graduate-level knowledge. They’ve come a long way in just a few years, and they’re only going to get better.” MEDIA & COMMUNICATIONS “Coretek partners with telecommunications providers to modernise network operations and reimagine customer engagement using Microsoft’s cloud and AI stack. By deploying Microsoft Copilot Studio virtual agents and Azure AI services, we enable intelligent support automation, predictive network management and hyper-personalised service recommendations. A large telecom provider in the mid-west US implemented an agentic AI solution that deflected 45 per cent of inbound support contacts through intelligent virtual agents while cutting mean resolution time by 30 per cent. Employees transitioned from reactive troubleshooting to proactive value delivery – demonstrating how AI-driven modernisation reshapes both operational efficiency and competitive customer experience simultaneously.” Brian Barnes Chief Technology Officer, Coretek We asked Microsoft partner Coretek how it is using cloud and AI solutions to help telecommunications providers enhance their operations Partner perspective Photo: iStock/ArtistGNDphotography
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