When Should AI Make The Decision?

Artificial Intelligence is becoming part of almost every discussion in telecommunications.

• AI-RAN.
• rApps.
• xApps.
• Closed-loop automation.
• Autonomous Networks.

But I believe we’re asking the wrong question. The real question isn’t: “Can AI make network decisions?” It already can. The real question is: “When should AI make the decision?” After more than two decades working in RAN optimization—from manual RF optimization, through cSON, and now Network Automation—I’ve learned that not every decision carries the same level of risk. Some decisions are repetitive. Others are strategic. And treating them the same way is a mistake. I see network decisions falling into three categories.

• Low-risk decisions These are repetitive, well-understood actions supported by clear policies. Examples include neighbor optimization, parameter consistency checks, PCI conflict detection, load balancing adjustments, or routine anomaly detection. Here, AI can often react faster and more consistently than any engineer. Automation delivers immediate value.

• Medium-risk decisions These involve multiple KPIs, conflicting objectives, or uncertain network conditions. AI can analyze thousands of possible scenarios in seconds, identify patterns that humans might overlook, and recommend the most promising actions. But at this level, I still believe engineers should validate the recommendation before execution. The best outcome comes from collaboration—not replacement.

• High-risk decisions Large-scale parameter changes. Energy-saving strategies affecting nationwide performance. Mobility policy redesign. Massive optimization campaigns. Actions with significant customer or business impact. These decisions require more than data. They require context. Business priorities. Operational experience. And sometimes intuition developed over years in the field. This is where human expertise remains essential.

To me, the future of Network Automation is not about removing engineers from the decision loop. It’s about placing them at the right point in the decision loop. AI should automate what is predictable. Engineers should guide what is uncertain.

The most successful autonomous networks won’t be the ones where AI makes every decision. They will be the ones where AI knows which decisions it should make—and which ones it should leave to experienced engineers. That balance, in my opinion, is what will define the next generation of intelligent RAN.

What do you think? Where would you draw the line between AI-driven decisions and human expertise in network operations?

#AI #AIRAN #NetworkAutomation #OpenRAN #SMO #rApps #xApps #SON #5G #Telecommunications #ArtificialIntellige