A Digital Twin Is Only Useful If It Keeps Up With Reality

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We talk a lot about creating a digital representation of the network. I think we need to spend just as much time talking about what happens the day after we create it. Networks don’t stay still. The physical environment keeps changing, work keeps happening and new information keeps coming in. The network record has to keep up.

A digital twin is only valuable if it has some relationship to what is actually happening in the field. That’s harder than it sounds in a fiber network. Construction moves. Conditions change. Inspections happen. Photos get taken. Records get updated—or don’t. Before long, the digital representation and the physical network can start telling different stories.

This is an area where I think AI can be genuinely useful. It can help compare the network record against field photos, inspection records, construction updates, public data, private imagery and other operational information. Instead of waiting for someone to discover a discrepancy manually, we can start identifying where information appears to be missing or where the real-world condition has changed.

That doesn’t mean AI gets to decide what is true. There still needs to be a reliable process for validation, particularly when the information affects construction, safety, cost or customer commitments. But it can make discrepancies much easier to find.

The bigger opportunity isn’t simply creating a better digital twin. It’s keeping the twin connected to reality as the network changes. A beautiful representation of what we thought was true six months ago isn’t operational intelligence. It’s history.

For me, that’s where the conversation about digital twins gets much more useful. The goal isn’t to create the most complete picture of the network once. It’s to create a network record that can continue to earn our trust. AI can help us identify where reality and the record have started to separate, but people still have to determine what happens next.