A new operational model driven by software, automation, and artificial intelligence is emerging as a critical pathway for telecom operators seeking efficiency and growth, according to Sam Keys Toyer, Global Head of Portfolio for Network Managed Services at Ericsson.
Speaking on the evolution of network management, Toyer explained that the company is shifting away from traditional approaches centred on spectrum and hardware upgrades, instead focusing on AI-led operations to manage increasingly complex network environments.
Ericsson’s managed services business now spans mobile, fixed, cable, and IoT networks, often across multi-vendor ecosystems. The core proposition, Toyer noted, is to operate networks on behalf of communications service providers (CSPs), delivering improved availability, enhanced performance, and reduced costs.
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However, he acknowledged that this mandate has grown more complex as networks evolve. “We started with automation and data foundations,” Toyer said. “The next step was applying machine learning to predict faults before they happen. Now, we’re moving into systems that can make complex decisions.”
To address this complexity, Ericsson has restructured its operational model around the Ericsson Operations Engine, a framework that integrates people, processes, tools, and security into a unified delivery system. Central to this approach is data-driven operations supported by large-scale automation.
According to Toyer, the company currently runs tens of thousands of automated processes every second across global contracts, with about 80 per cent of operational tasks incorporating some level of automation. He stressed, however, that the industry’s focus is now shifting from automating tasks to enabling intelligent decision-making.
This transition aligns with the broader industry push toward autonomous networks, where systems can analyse, decide, and act with minimal human intervention. Working alongside frameworks developed by organisations such as the TM Forum, Ericsson is targeting higher levels of operational autonomy.
A key component of this evolution is intent-based operations, where operators define desired outcomes rather than specific instructions. The system then determines how best to achieve those objectives.
Toyer highlighted energy optimisation as a practical example, explaining that operators can set an “intent” to reduce power consumption without compromising user experience. The system continuously monitors network conditions, predicts necessary adjustments, and executes them automatically.
He also pointed to service assurance use cases, where operators can define quality benchmarks for platforms like YouTube and WhatsApp during peak traffic periods. The network can then dynamically reallocate resources, test potential solutions—including through digital twin simulations—and implement optimal configurations in real time.
Despite these advances, Toyer emphasised that transparency and human oversight remain essential. Observability layers, audit trails, and “human-in-the-loop” controls are built into the system to ensure accountability and build trust in AI-driven processes.
“We’re still in the early stages,” he said. “But when you can show how these systems work, and provide the right level of explainability, confidence builds.”
He acknowledged that AI is increasingly entering areas traditionally reserved for human judgement, particularly in managing complex trade-offs within network operations. Ericsson’s strategy combines machine learning with advanced reasoning techniques and agent-based models to improve contextual decision-making.
Nevertheless, Toyer was clear that automation is designed to augment, not replace, human expertise. “Humans are not leaving the loop,” he stated. “This is about using machines to increase productivity and handle complexity, while people focus on higher-value activities.”
As telecom networks become more programmable and service-oriented, the ability to manage complexity at scale is expected to play a pivotal role in unlocking new revenue streams, especially in enterprise and private 5G deployments.
For Ericsson, operational transformation represents the missing link between 5G capability and commercial success. While the technology can already support differentiated services, its complexity has slowed widespread monetisation.
“If we can simplify how networks are operated,” Toyer said, “we open the door to the full promise of 5G service diversity, differentiated connectivity, and ultimately, new revenue.”
With the telecom industry continuing its search for sustainable growth, the effectiveness of AI-driven network operations may prove decisive in delivering that promise.
