Look, we’ve all been there, stuck on a call with a “smart” assistant that’s about as bright as a broken lightbulb. You’re screaming “Operator!” into your phone while the robot just keeps looping the same three options.
Most people blame the AI’s “brain” for being glitchy, but here is a little secret from behind the scenes: a lot of the time, the AI is actually doing its job just fine. The real problem is the invisible “pipes” that carry the voice from your mouth to the server. This is what the tech geeks call routing and termination, and honestly, most companies are still using old, rusty pipes for brand-new, high-tech AI.
If the connection is laggy or the sound quality is crunchy, the AI can’t understand you, it gets confused, and the whole conversation falls apart. It’s like trying to have a deep, philosophical discussion over a walkie-talkie with dying batteries. In 2026, if your team isn’t checking the “plumbing” of your voice setup, you’re basically throwing money into a black hole.
So, let’s stop guessing why our callers are hanging up frustrated. Here are 10 questions your team needs to ask right now to make sure your Voice AI actually works like it’s supposed to.
Why “Good Enough” Phone Lines are Killing Your AI
Before we get into the audit, we have to realize that the rules have changed. Back in the day, a “good” phone connection just meant you could hear the other person without too much static. But in 2026, “standard” VoIP just doesn’t cut it anymore.
To make an AI sound like a real person, you need two things: zero lag and perfect sound. If the connection isn’t “lossless” (which just means none of the audio gets squished or lost), the AI starts to lose its “human” magic. It’s the difference between talking to a friend and talking to a glitchy computer from twenty years ago.
There is a lot of money on the line here, too. Experts say that by the end of this year, AI voice traffic could save businesses around $80 billion in labor costs. That is a massive number! But there is a catch: those savings only happen if the “hand-off” works. If the call drops or the AI gets confused because of a bad connection more than 2% of the time, the whole system breaks down and customers get mad.
Our goal is to move past just “making the phone ring.” We need to focus on something called high-fidelity stream management. This is just a fancy way of saying we need to treat every voice call like a high-quality data stream that has to be perfect every single second. If the stream is messy, the AI is messy. It is that simple.
The Audit – 10 Questions Every Team Must Ask
1. What is our P.562 (MOS) score for AI-to-PSTN termination?
The first thing your team has to check is something called the MOS score. Think of this like a grade on a report card for how good a phone call sounds. It goes from 1 to 5, and if you are running a Voice AI, anything below a 4 is basically a failing grade.
Here is why this matters so much. When you talk to a human on a fuzzy phone line, your brain is smart enough to fill in the gaps. If the signal cuts out for a split second, you can usually guess what the other person said. But an AI isn’t that patient or that clever yet. If the connection has “packet loss” (which is just a fancy way of saying bits of the audio are getting lost in the mail), the AI gets confused.
It’s like trying to read a book where every fifth word is blacked out. You might get the gist of it, but you’ll probably mess up the details. When the audio is crunchy or cuts in and out, the Speech-to-Text engine starts making weird guesses. This is how a customer asking about a “billing statement” ends up being heard by the AI as “filling basement.”
So, you have to ask your team: What is our MOS score for calls going out to the regular phone network? If the answer is “we don’t know” or “it’s around a 3,” then you have a major problem. You are basically giving your expensive, high-tech AI a bad pair of ears. You can have the smartest AI in the world, but if the “termination” (the way the call connects to the phone lines) is low quality, your bot is going to look really dumb, really fast. It is a total waste of money to build a genius AI and then give it a cheap, fuzzy connection to talk through.
2. Is our SIP signaling optimized for <200ms TTFB?
The second big question is all about speed, but not the kind of speed you think. We are looking at something called “Time to First Byte” or TTFB. In simple terms, this is the time it takes for the very first tiny bit of data to travel from one point to another once a connection starts.
Think about when you ask a question and there is that awkward silence before the other person answers. If that silence lasts too long, it feels weird. In the world of Voice AI, we call this the “uncanny valley.” If the delay is more than 800 milliseconds, your brain immediately screams “This is a robot!” and you stop trusting the conversation.
The problem is that the AI already has to spend time “thinking” to come up with an answer. If your phone routing system takes 300 milliseconds just to get the signal moving, you are already halfway to that “creepy robot” limit before the AI even starts to process the words. You really want your system optimized to under 200 milliseconds for that first bit of data.
You need to ask your team: Is our signaling fast enough, or are we making the AI look slow? If your tech setup is laggy, it does not matter how fast your AI is. The customer is going to feel like they are talking to someone on a long-distance radio from the 1940s. It just feels clunky and unnatural. If you want people to actually enjoy talking to your AI, you have to trim the fat off that connection time.
3. Are we utilizing “Barge-in” capable SIP trunking?
Next up is something that sounds a bit aggressive but is actually just about being polite. It is called “Barge-in” capability. You know how when you are talking to a friend and you suddenly remember something, so you jump in and say “Oh wait!” and they stop talking? That is a natural human conversation.
The problem is that a lot of older phone setups are “half-duplex.” This is just a fancy way of saying only one person can talk at a time, like those old walkie-talkies where you have to say “over” and wait for the other person to finish. If your system works like that, your AI is going to be a total chatterbox that just keeps blabbing even when the customer is trying to say something important.
You have to ask: Can our system handle two people talking at the same time? This requires “full-duplex” audio streams. Without it, your AI is basically wearing noise-canceling headphones. If a customer says “No, that is not what I meant!” and the AI just keeps reading a script for another thirty seconds, the customer is going to get annoyed and probably just hang up.
It really comes down to manners. If your routing and termination setup does not support barge-in, your AI looks rude and robotic. You want the AI to be a good listener, not just a good talker. Making sure your tech can “hear” while it “speaks” is the only way to make the experience feel like a real conversation instead of a frustrating lecture.
4. How are we handling PII Redaction at the Gateway level?
Now we have to talk about something a little scary: private information. When a customer calls in and starts rattling off their credit card number or their social security number, that data is like a hot potato. You don’t want it sitting around where it shouldn’t be.
This is where “PII Redaction” comes in. PII just stands for Personally Identifiable Information, and redacting it means blacking it out so nobody can see it. The big question for your team is: Are we catching this private stuff at the front door?
In a perfect world, your “gateway” (the tech that sits between the phone line and your AI) should be smart enough to hear a credit card number and mask it right away. This way, the sensitive numbers never even reach the AI’s brain or get written down in a transcript. If your system doesn’t do this, you’re basically leaving the front door to your house unlocked.
Think about the “Session Border Controller” or SBC. It is like a security guard for your phone calls. You want that guard to be able to spot a credit card number and scrub it out before it goes any further. If you’re just sending all that raw, private data straight to the AI, you are asking for a massive headache with lawyers and privacy rules later on. It is much better to be safe and strip that info out at the very start of the route.
5. Do we have “Carrier Grade” redundancy for AI-Agent Failover?
Next up is the “what if” plan. Imagine your main AI system just decides to take a nap or the connection to it drops. If you don’t have a backup, the call just goes dead. That is a huge problem because a dropped call is the fastest way to lose a customer’s trust.
You need to ask: Do we have a carrier-grade failover plan? This is basically a “Plan B” that kicks in automatically. If your primary route gets clogged or goes down, your system should be smart enough to instantly send that traffic somewhere else, like a backup AI or even a human team.
Data shows that most big business crises happen because of downtime. If you aren’t using “redundant” routes (which is just a fancy way of saying you have more than one path for the call), you are basically walking a tightrope without a net. It is way better to have a backup ready and never use it than to need it and have nothing but silence on the other end.
6. Are we using G.711 or Opus for high-fidelity ASR?
Moving on to question six, we have to look at the “codecs” we are using. Think of a codec like the resolution on a YouTube video. If you watch a video in 144p, everything is a blurry mess. In the voice world, using an old codec like G.729 is like that blurry video. It squishes the audio so much that the AI can’t tell the difference between “S” and “F” sounds. You need to ask: Are we using high-quality audio like Opus or G.711? If you give the AI high-definition sound, it stops making those annoying “I didn’t catch that” mistakes.
7. What is our “Containment-to-Termination” Ratio?
Seventh, you need to check your “Containment-to-Termination” ratio. This is basically a scorecard of how many people the AI actually helped versus how many people got frustrated and asked for a human. If everyone is hanging up or hitting zero to escape the bot, your routing logic is probably broken. A good goal for 2026 is for the AI to handle about 70% of the easy stuff on its own. If your numbers are way lower, the AI might be getting the wrong calls sent to it.
8. Is our STIR/SHAKEN attestation hurting our Outbound AI?
Question eight is about “STIR/SHAKEN.” It sounds like a James Bond drink, but it is actually a system that proves your call isn’t a scam. If your AI is calling out to customers and your “attestation” (your identity check) is low, their phones will just label you as “Spam Likely.” Nobody answers those. You have to ask: Is our outbound caller ID verified? If you are paying for an AI to make calls that nobody picks up, you are just burning cash.
9. Can our infrastructure handle “Elastic Scaling” for flash traffic?
Ninth, let’s talk about “Elastic Scaling.” This is just a cool way of saying your system can stretch. If you suddenly get 10,000 calls at once because of a big sale, can your phone lines handle it? You need to ask: Can our infrastructure grow in seconds? If your system hits a limit and starts giving people a busy signal, your “smart” AI setup is going to look like a joke.
10. Are we auditing “Silent Seconds” in the routing path?
Finally, question ten: Are we auditing “Silent Seconds”? This is the dead air that happens while the call is being routed. Even two seconds of silence feels like an eternity on the phone. If there is a gap between the customer finishing their sentence and the AI starting its answer, the customer will think the call dropped. You need to hunt down those silent gaps in your routing path and kill them. If the conversation doesn’t flow, people won’t use it.
Performance Benchmarks for 2026
| Metric | Target | Impact Area |
| End-to-End Latency | < 800ms | User Satisfaction (NPS) |
| Packet Loss | < 0.5% | Speech Recognition Accuracy |
| Jitter | < 20ms | Natural Voice Fluidity |
| ASR Word Error Rate (WER) | < 5% | Transaction Success |
Bottom Line
So, here is the bottom line: your AI is really only as good as the “wire” it travels on. You could spend millions of dollars building the smartest, most helpful AI brain in the world, but if the phone lines carrying its voice are old and glitchy, nobody will ever know.
Think of it like putting a Ferrari engine inside a rusty old golf cart. It might be powerful, but it is not going to go anywhere fast, and the ride is going to be terrible. By asking these ten questions and auditing your routing and termination, you are making sure your high-tech AI isn’t being held back by old-school phone problems.
In 2026, the companies that win are not just the ones with the best AI, but the ones who actually make the conversation feel easy and real. If you take care of the “plumbing” and the technical backbone, your AI can finally stop sounding like a robot from a 1950s movie and start sounding like a real solution for your customers.
Perfect your Voice AI at the onset
If all of this sounds a bit overwhelming, don’t worry, you don’t have to rebuild your entire phone system alone. This is exactly what we do at IDT Express.
We provide the high-quality “pipes” that make your Voice AI actually sound smart. Whether you need crystal-clear audio quality to help your AI understand every word, or super-fast connections so there is no awkward lag, we have you covered. We make sure your calls get where they need to go without the “creepy robot” glitches.
Ready to give your AI the voice it deserves? Check out IDT Express and see how our global network can make your Voice AI routing and termination rock solid. Stop letting bad connections ruin your good ideas.
