Comparing live pricing and terms from 400+ carriers and platforms
Most AI projects get budgeted like software and fail like infrastructure. Three questions tell you which side of that line you are on: where the traffic goes, what happens when the circuit drops, and who is on the hook for the data.
Most AI projects get budgeted like software and fail like infrastructure. Two industry surveys this year put numbers on it: Cisco's AI Readiness Index found only 15% of organizations have networks flexible enough to run AI at scale, and Broadcom's 2026 State of Network Operations found that fewer than half — 49% — believe their network can carry the bandwidth and latency AI needs. Before you sign anything, three questions will tell you which side of that line you're on: where does the traffic actually go, what happens when the circuit drops, and who is legally on the hook for the data.
I get a version of the same call every few weeks now. Somebody's been asked to "figure out AI" for the business. They've priced the software. They've watched the demo. What nobody in the room has asked is whether the building can carry it.
That's not a criticism. AI gets sold like software — a per-seat number, a login, a start date. So it gets evaluated like software. But it behaves like infrastructure, and infrastructure fails differently. Software fails loudly, on day one, and you get a refund. Infrastructure fails quietly, in month four, on your busiest day, and there's nobody to hand the bill to.
Here's the order I'd ask things in.
Almost every AI tool a normal business buys is somebody else's computer. The model doesn't live in your office. Every prompt, every document you point it at, every transcription of every meeting — that's a round trip out your circuit and back.
So the question isn't "how fast is our internet." It's "how fast is our internet in the direction we're about to start using."
Most business connections are asymmetric, and the asymmetry is aggressive. A connection sold as 500 down might be 35 up. That was a perfectly sensible trade when your traffic was people reading email and pulling up web pages. It stops being sensible the week you start pushing documents, recordings, and video into a model all day. Upstream is the lane that fills first, and it's the number nobody reads on the contract.
The survey work backs up the instinct. Cisco's AI Readiness Index put the share of organizations with networks flexible enough to support AI at scale at 15%. Broadcom's 2026 report found 49% believed their network could handle AI's bandwidth and latency demands — which is another way of saying more than half of the people already doing this don't think their own network is ready.
What I'd actually do: pull your last bill and find the upload number, not the download number. Then find out what your real usage is today. If you don't have that data, that's the finding.
This is the one that turns an AI project from a productivity story into an operations problem.
When AI is a novelty, an outage is an annoyance — people go do something else for an hour. Once it's in the workflow, an outage is a work stoppage. If your quoting, your scheduling, your intake, or your support desk routes through a tool that lives on the other end of one circuit, then that circuit just became load-bearing for the business in a way it wasn't last year.
A lot of Ohio businesses I walk into have exactly one path out of the building. Sometimes they have two, from two different logos, that a look at the physical route says share the same conduit at the street — which means one backhoe takes both. Diversity on the invoice isn't diversity in the ground.
The fix isn't automatically expensive, and it's usually not the fix people expect. Sometimes it's a genuinely diverse second path. Sometimes it's wireless failover that costs very little and only earns its keep twice a year. Sometimes the honest answer is that the workflow shouldn't depend on the tool that hard yet, and the right move is to change the workflow, not the circuit.
What I'd actually do: name the three processes that would stop if the internet went down for four hours. If AI is about to sit inside any of them, price failover before you price seats.
Every AI tool has an answer to "what do you do with what we put in." The answers differ enormously, and they're rarely on the pricing page.
The specific things worth reading for: does your input get used to train the vendor's models, and can you turn that off. How long is data retained after you delete it. Where is it processed geographically. And if you're in a regulated lane — healthcare, financial services, anything touching payment data, anything with a government contract — does the vendor sign the agreement your regulator expects, or do they just say they're "compliant."
I'd also check with your cyber insurance carrier before you deploy, not after. Renewal questionnaires have been getting sharper about AI tooling, and the time to discover a gap is not during a claim.
What I'd actually do: get the vendor's data-handling terms in writing, and send them to whoever signs your insurance renewal. If nobody in your organization owns that question, that's the finding.
Buckeye Telecom is a broker. We've been owner-led and family-owned in Columbus since 2003, and we work across more than 400 suppliers. You don't pay us — the carriers do. That arrangement is the reason I can write a post whose honest conclusion is sometimes "you're fine, don't buy anything."
Because that is sometimes the conclusion. Plenty of businesses ask these three questions and find out their network is in decent shape and their AI plan is modest enough not to strain it. Good. That's a real answer, and it took an afternoon instead of a failed rollout.
The businesses that get hurt aren't the ones that move slowly. They're the ones that discover in month four that the pilot everybody liked can't scale past the building it's in.
Ask the three questions first. Most of the cost of getting this wrong is in the order you did things.
Want a structured version of this? Our 3-minute readiness scorecard walks the same ground and gives you something to hand your team: take the scorecard.
Cisco AI Readiness Index (2025) — share of organizations with networks flexible enough to support AI at scale: 15%.
Broadcom, 2026 State of Network Operations — 49% say their networks can support AI bandwidth and latency requirements.
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