When companies talk about becoming “AI-ready,” they usually jump straight to software: which tools to deploy, which models to use, and how to train employees. Doug Roberts thinks that’s backwards. The first real test of readiness, he says, is whether a business can move data reliably—every day, under load, without surprises.
Roberts, Cytranet’s Chief Technology Officer, has spent the last year watching a clear pattern emerge across businesses adopting AI and cloud-heavy workflows: the network is no longer background infrastructure. It’s becoming the limiting factor—or the accelerator—depending on how it’s built.
“AI turns the internet connection into a business system,” Roberts said in an interview. “When you introduce AI, you increase data movement, you increase monitoring and logging, and you increase sensitivity to latency and instability. A connection that felt ‘fine’ a year ago can suddenly feel like the biggest problem in the building.”
That shift is one reason Cytranet has been leaning harder into business-only fiber connectivity and deeper ties to data center routes. The company’s expansion strategy, Roberts says, is aimed at one thing: giving organizations the kind of predictable bandwidth that modern workloads demand.
The Newsworthy Change: “Business Internet” Is Being Reclassified Inside Companies
Roberts believes the most significant development isn’t a single new technology—it’s the way businesses are changing how they evaluate connectivity. Instead of treating internet service as a commodity, many are approaching it like an operational risk category.
He says he now hears questions that used to be rare outside of large enterprises: What does performance look like at peak usage? How strong is upstream capacity? What are the redundancy options? How does incident communication work? What’s the path to direct connectivity into data centers and cloud on-ramps?
“You can tell when people have been burned,” Roberts said. “They stop asking about the advertised speed and start asking what happens when the network is stressed.”
For companies integrating AI, stress is no longer occasional. It’s routine. Even businesses that aren’t training models internally are moving more data and running more always-on services than they did just a couple of years ago.
AI Is Making Upload Capacity a Bigger Deal Than Most People Expect
One of the points Roberts returns to repeatedly is how AI and cloud operations quietly shift bandwidth in a direction many organizations don’t plan for: upstream.
It’s not just file uploads. It’s continuous syncing between systems, security telemetry, backups, collaboration tools, application monitoring, and the constant exchange of data with cloud compute environments.
“Businesses still think in download terms because that’s how the consumer world talks about internet,” Roberts said. “But modern business operations—especially AI workflows—are extremely upload-heavy. If your upstream is constrained, your cloud becomes slower, your backups become longer, and your analytics pipelines become unpredictable.”
That unpredictability, he says, is exactly what businesses can’t afford once AI becomes embedded in daily operations. A delayed dataset transfer or an unstable link to cloud services isn’t just inconvenient—it affects production, decision-making, and customer-facing systems.
Data Centers Are Showing Up in Conversations That Used to Be About Offices
Perhaps the most interesting shift Roberts described is how often data centers are now part of everyday business planning. Not just for software companies, but for organizations in logistics, healthcare, professional services, media, and education.
He attributes this to a growing awareness that compute is no longer abstract. AI workloads, especially, push businesses to think about where processing happens and how efficiently they can reach it.
“Businesses are building hybrid environments whether they call them that or not,” Roberts said. “They have some systems local, some in the cloud, and increasingly some in colocation or specialized compute environments. The network is the connection between those worlds.”
As AI moves from experimentation to production—whether it’s customer support automation, real-time analytics, predictive operations, or document processing—the connection to compute has to be stable and fast. Latency spikes and inconsistent throughput start showing up as real operational problems.
“You don’t need to be a data center operator to care about data centers anymore,” Roberts said. “You just need to run a modern business.”
Why Fiber Matters: Consistency, Not Just “Fast”
Roberts doesn’t treat fiber as a buzzword. He describes it as a practical foundation that makes performance more consistent and scaling simpler.
“Businesses operate under load,” he said. “Voice systems, video calls, security tools, cloud apps, backups, and now AI-driven processes running constantly. Fiber gives you a more predictable platform for those realities.”
In his view, the real advantage of fiber is how it performs when it’s busy—when the network is carrying real traffic from real operations. That’s when businesses notice the difference between infrastructure designed for modern demand and infrastructure that has been extended and patched over time.
“Speed tests don’t run your business,” Roberts said. “Consistency does.”
Cytranet’s Approach: Business and Enterprise Only
Cytranet’s strategy is shaped by a choice Roberts sees as increasingly important: the company doesn’t serve residential customers. It focuses entirely on business and enterprise connectivity.
That decision, he says, isn’t about exclusivity. It’s about alignment.
“Residential service is built around a household experience and mass-market scale,” Roberts said. “Business connectivity is about engineered performance, support urgency, and accountability. Those are different worlds, and we’ve chosen to specialize.”
Because the company is business-only, Roberts says, its network planning and support operations are designed around the reality that downtime costs money and disrupts operations. Customers aren’t buying a bundle—they’re buying reliability.
What Businesses Want Now: A Network They Don’t Have to Think About
When asked what customers are seeking most, Roberts didn’t start with speed. He started with confidence.
“They want to stop worrying,” he said. “They want to know the network will support growth, support cloud adoption, support AI tools, and support the day-to-day reality of modern work.”
In practice, that translates into businesses looking for scalable bandwidth, clean paths to data center ecosystems, and providers who communicate clearly when something breaks.
“No one expects perfection,” Roberts said. “But they do expect transparency and competence—especially when the network is critical.”
The Broader Implication
Roberts believes this shift will reshape how regions compete for growth. As more companies rely on AI and data-heavy operations, the availability of business-grade fiber and strong connectivity to compute hubs becomes a factor in where businesses expand.
The hype around AI is loud, he said, but the real differentiator will be quieter: whether companies can operate reliably on the infrastructure beneath it.
“If you want to move fast with AI, you need the basics to be strong,” Roberts said. “Fiber, bandwidth, stable connectivity into compute environments—those are the things that turn AI from an idea into an everyday capability.”
And for Roberts, that’s the news: as AI adoption accelerates, business internet is no longer just “internet.” It’s the backbone of competitiveness.
