- In 2026, IQGeo commissioned a survey of 500 telecom decision-makers
- The survey asked operators how they track their physical network assets
- And a surprising percentage said they are still using spreadsheets and paper
IQGeo, a developer of geospatial software for telecom companies, says that the degree to which an operator’s physical network records match what is actually in the ground is becoming a problem for the telecom industry.
According to IQGeo, “As telecom operators invest in automation, AI and autonomous network operations, every decision those systems make is only as reliable as the physical network data underneath.”
In fact, Fierce Network has been writing for quite a while about the serious problem that telcos with lots of technical debt are going to face if they want to tap AI.
In 2026, IQGeo commissioned the independent technology research firm Vanson Bourne to conduct a survey of 500 telecom decision-makers across the U.S., Canada and U.K. to determine the extent of their “ground truth,” as it calls it. Respondents represented mobile, fixed broadband and wholesale operators.
When asked how their organizations primarily maintain records about their physical network assets, 50% of respondents said they keep records across multiple systems; while 24% said they use spreadsheets, CAD systems or paper-based records! Only 25% said they use a single, integrated geospatial system.
Perhaps more telling, was the question: How long has your organization used your current network management software?
Only 4% said they had a new system 5-years-old or less. The majority of telcos were using systems from 5-20 years old.
The survey asked what percentage of an operator’s network records were currently accurate and up to date. And the vast majority said their records were 26%-75% up to date. Only 13% of respondents said their “ground truth” was 76%-100% accurate
From a bigger perspective, operators were asked what they think is standing in the way of autonomous operations. The biggest obstacle was (not surprisingly) money, with 50% of respondents citing budget constraints. But other factors included legacy systems that are difficult to modernize and lack of integration between systems.
According to IQGeo, poor physical data quality not only hampers the ability to move to AI and automation, but it makes companies less appealing as acquisition targets.
David Cottingham, CTO at IQGeo, said, "Operators, AI systems, investors and acquirers all need accurate, complete records of the physical network to make decisions. This research shows most operators are a long way from that. I think it’s very telling that, when we asked operators where AI will deliver the most value, the number one answer was improving the accuracy of their records, ahead of predictive maintenance and network optimization.”
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