AI Ambitions Are Running Into a Network Infrastructure Trust Problem
Enterprise ambitions around AI are running into a fundamental problem: Orgnanizations aren't always confident in the networks those projects depend on, according to a report from telecommunications provider Arelion.
The research found that concerns about network providers have caused organizations to rethink strategic initiatives over the past two years. Among respondents whose initiatives were affected, AI and data-driven projects were the most cited, at 49%. That put AI ahead of security and compliance programs at 44%, digital transformation at 42%, and cloud migration at 38%.
The findings come from Arelion's report, "The Trust Illusion: Why AI and Digital Transformation Need More Than a Reliable Network," based on a survey of 518 senior enterprise network decision-makers in the U.S., U.K., Germany, and France conducted by Savanta.
All respondents worked for organizations with more than 2,000 employees and influenced network strategy across data centers, cloud, and connectivity. Of those surveyed, 66% had final sign-off responsibility. The results suggest that as organizations pursue increasingly data-intensive AI projects, confidence in the network infrastructure supporting them could become another deployment obstacle.
Trust Looks Different When Something Goes Wrong
On the surface, Arelion found little evidence of a trust crisis. A total of 93% of respondents said they largely or completely trust their current network provider, while 83% said that trust has strengthened over time.
The picture changes when respondents are asked about a serious network incident. Only 15% said they have complete confidence in their provider's ability to quickly detect and address such a problem. Another 42% said their provider seriously lets them down anywhere from a few times a year to monthly or more frequently.
Those concerns have consequences beyond the network itself. Responding organizations have delayed, scaled back, or stopped strategic initiatives because of provider trust concerns, while others have added resiliency or risk-mitigation measures.
AI and data projects were the most affected among respondents reporting an impact, as organizations try to move AI from experimentation into larger production deployments.
A serious provider failure could also have substantial consequences. Forty percent of respondents said such an event would cause major operational disruption, while 18% anticipated significant financial loss or severe financial or reputational damage.
AI Creates a Second Trust Problem
Another tension runs through Arelion's findings. Enterprises need networks they can trust to support AI projects, but many of the same decision-makers are concerned about AI's growing role inside those networks. A total of 54% of respondents identified AI and automation in network management and security as the factors most likely to negatively affect network trust over the next three years. That ranked ahead of data sovereignty expectations and geopolitical instability, both at 39%, and regulatory requirements and quantum computing threats to current encryption standards, both at 38%.
At the same time, respondents aren't rejecting AI as a network technology. Proactive AI-driven fault prediction was among the capabilities they said would matter most to future trust, alongside stronger built-in security, greater accountability, and responsive support. That leaves enterprises in an unusual position: AI is increasing their dependence on digital infrastructure while also raising questions about how that infrastructure itself is managed.
Arelion has an interest in emphasizing the importance of network-provider trust, and the survey reflects the views specifically of network decision-makers at large enterprises. Still, the findings point to an infrastructure consideration that can get lost amid the rush to adopt new AI models and agents. AI projects ultimately depend on the networks, cloud environments, data centers, and connectivity beneath them. If organizations lack confidence in that foundation, access to better AI models alone won't remove the obstacle.
"Trust is influencing which strategic initiatives move forward, how organizations manage risk, and which providers they choose to work with," said Mattias Fridström, Vice President at Arelion. "As businesses become increasingly reliant on digital infrastructure, enterprises are looking for network providers that can demonstrate transparency, accountability, and operational excellence, not just availability."
The full report is available for download here at the Arelion site (registration required)