Why SMO Alone Will Not Create An Autonomous Network

“Deploying an SMO is an important milestone. Achieving network autonomy is something entirely different.”

As the telecom industry embraces O-RAN and intelligent automation, the Service Management and Orchestration (SMO) platform has become one of the most talked-about components. Sometimes, it’s even presented as the missing piece that will finally enable autonomous networks. I don’t see it that way. An SMO is a powerful enabler. But by itself, it cannot make a network autonomous. Why? Because autonomy is not a product. It’s an ecosystem.

In my experience, achieving meaningful automation requires much more than deploying a new management platform. It requires connecting technology, processes, data, and engineering expertise.

Consider what is really needed:

• High-quality, trustworthy data collected consistently across RAN, transport, and core domains.
• Clearly defined automation policies that determine when the network should act automatically and when human intervention is still required.
• Reliable rApps, analytics, and AI models capable of generating recommendations that are technically sound and operationally safe.
• Engineers who understand not only how the platform works, but also the operational impact of every automated decision.

Without these elements, an SMO becomes another management system rather than an automation platform. One lesson I’ve learned while working on network automation initiatives is that the hardest challenge is rarely the software itself. It’s building confidence. Confidence in the data. Confidence in the automation logic. Confidence that the recommended action will improve the network instead of creating new problems.

That’s why I believe the journey toward autonomous networks will happen in stages. First, operators automate repetitive tasks. Then, they automate low-risk optimization decisions.

Only after earning operational trust can they move toward closed-loop automation with minimal human intervention. Technology will continue to evolve. SMO capabilities will mature. AI models will become more accurate.

But engineering judgment will remain essential for defining the rules, validating outcomes, and continuously improving the automation process. An autonomous network is not created by installing an SMO. It is created by combining architecture, data, automation, and experience into a system that operators can truly trust.

What’s your perspective? Is the biggest challenge in autonomous networks the technology itself, or building enough confidence to let automation make operational decisions?

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