- The vast majority of rural broadband operators still lack a clear AI strategy
- More than half say they feel behind as AI adoption accelerates
- Experts say providers should start with business problems, not the tech
The AI race is on, and tier-1 operators are already touting their leads. But many rural broadband providers say they’re still stuck at the starting line.
A recent survey of 132 rural operators found 82% have no clear or defined AI strategy and 49% have only limited or informal adoption of the technology. It’s no surprise, then that 56% of the operators surveyed – and 66% of small, rural providers with fewer than 10,000 subscribers – said they feel like they’re behind with AI.
But Glen Paul, sales director at Innovative Systems, said during a webinar this week covering the report that this perception isn’t necessarily reality. Innovative Systems is the vendor that commissioned the report.
“There’s a lot of buzz about AI but really only 1% of operators across the country have actually implemented AI into their actual workflows, working more into that agentic state,” Paul said. “The perception of AI being everywhere is just that – a perception right now. The reality is we’re at the very forefront of AI and how we’re going to be using AI.”
Realities of the AI landscape today
According to the report, rural operators are most commonly using AI for internal knowledge-based search (43%), targeted marketing (39%), threat detection (27%) and network monitoring (24%). Though operators generally catch a lot of flak for using AI in customer service, rural operators have bene much slower to move on this front with only 14% leveraging chatbots, 12% using service assistants and 15% using AI for call quality assurance.
“All the companies that we talked to are looking to implement AI, they want to use more AI, but what we’re finding is there are some roadblocks in there,” Paul said.
Among the hurdles to broader AI adoption, 68% cited a lack of internal skills or confidence, while another 53% pointed to uncertainty about vendors and tools. Safety and regulatory concerns (38%), a lack of documentation around processes that could be automated (37%) and resistance to change (37%) were also top challenges.
“People aren’t sure what they should be doing yet, or how they should be doing it, so they don’t want to touch AI,” Paul said, adding he was shocked to find only 29% had a concern about budget.
Playing AI catchup
Venu Amar, Chief Operating Officer, Actifai said during the session the best approach to getting started is to jump in and start using and talking about the technology.
He added that many businesses are used to looking at the technology as a starting point and working out use cases from there. But in forming an AI strategy, they should actually be doing the reverse.
“It’s really important as an organization not to work forward from the technology but to work backward from the business problem,” he said. “First and foremost, think about your core business problems and then work backwards to see is there an artificial intelligence technology – whether that’s agentic AI, large language models or machine learning algorithms or the like – that can actually solve that.”
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