Mike HeapMike is an experienced Product Manager who focuses on all the “non-development” areas of My AskAI, from finance and customer success to product design, copywriting, testing and more.
Table of Contents
- What does a standard AI vendor SLA cover, and what does it miss?
- What belongs in an AI customer service contract?
- Uptime: what counts as down, and what a credit pays
- Incidents: how fast you hear, and what happens to tickets meanwhile
- Resolution commitments: what to ask for and how to test it
- Data and exit: what you get back, what gets deleted, and how you leave
- What do real AI rollouts show about these terms?
- TravelJoy: switching AI on the same helpdesk
- Edel Optics: the rate moved when order data was connected
- A consumer AI-assistant app: a lower rate by design
- YouGarden: a vendor switch, then a month in notes mode
- What should you do this week?
- When does this advice not apply?
- The takeaway
- FAQs
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An AI customer service SLA should cover uptime, incidents, how resolution is measured, and your data at exit. Negotiate hardest on incident notice, a test on your own tickets, and exit terms.
Once a company passes about 150 people, the order form for an AI agent usually goes through legal and procurement, and it comes back with a question attached: what should the SLA say? By SLA (service level agreement) I mean the commitments your AI vendor makes to you in the contract; the reply-time targets your team works to are a separate document.
An AI agent can be fully up and still give customers a wrong answer, get worse after an update, or keep your conversation history after you cancel. A typical uptime-and-credit agreement was never written to catch any of that. Check the uptime figure and the service credit quickly, and spend your negotiating time on incident notice, a test on your tickets, and getting your data back when you leave.
I'm Mike, co-founder of My AskAI. We run AI agents inside Zendesk, Intercom, Freshdesk, Gorgias and HubSpot for 200+ ecommerce and SaaS businesses, so I'm on the vendor side of these contract reviews. Our agents have resolved over 1,000,000 tickets at a 72%+ resolution rate on a rolling 30-day basis, and we hold a 4.5/5 rating from 23 reviews on G2. If you're still choosing between vendors, our AI customer service vendor selection checklist covers the step before this one.
What does a standard AI vendor SLA cover, and what does it miss?
TL;DR: A standard SLA promises an uptime percentage and pays a small service credit when the vendor misses it. With AI, the failure a support team feels most is wrong or worse answers while the system is up, so the contract needs terms for that too.
The SLA most vendors hand you is the generic software one. It sets a monthly uptime percentage, a service credit worth a share of your fee if they miss it, and sometimes a target for how fast their support team replies to you. A large public cloud SLA follows the usual pattern (10% of the bill back below 99.99% monthly uptime, 30% below 99.0%, and the whole bill below 95.0%).
That pattern is reasonable, and for a team whose AI answers customers overnight with nobody behind it, I think uptime is the term that counts most.
Under many software SLAs the service counts as available if you can connect to it, even when it's missing functionality described in the documentation, as one law firm's guidance on SaaS contracts points out. So your AI agent can be 100% up while it hands out last season's refund policy for a week.
The model underneath an AI agent also changes often, and even a small update can alter how the agent answers overnight. None of that counts as downtime.
One analysis of AI vendor contract data found that only 17% of AI contracts promised the product works as documented, against 42% of SaaS contracts.
A credit also has to be claimed (usually before a deadline), and it can be refused. One IT admin posted the reply their team got after asking for a credit following a 10-hour outage:
"no service credits or financial compensation are being issued for this specific outage" u/alittle158 on r/sysadmin
In another thread, admins found that slow service had been left out of their SLA's definition of down, so nothing was paid at all. Our status page is public, so anyone looking at My AskAI can see how the service has been running before they sign anything.
What belongs in an AI customer service contract?
TL;DR: Four sets of terms: uptime, incidents, resolution commitments, and data and exit. Negotiate hardest on the terms that let you catch a problem early and act on it yourself; the ones that pay you back afterwards matter less.
The terms worth negotiating fall into two groups. Some pay you back after something has gone wrong, like the uptime percentage and the service credit. Others let you act yourself: being told about incidents and changes, measuring resolution on your tickets, and getting your data back and deleted when you go.
For a starting point, the EU publishes model contract clauses for buying AI (written for public-sector buyers), and a practical guide to those clauses notes that private companies are starting to use them as a reference too. Here is what to ask for under each set of terms, what it's worth to you, and what a reasonable answer from a vendor looks like.
Terms | What to ask for | What it is worth to you | A reasonable answer from the vendor |
Uptime | A monthly figure, a definition of "down" that includes the AI failing to reply, and credits that apply without a claim | Tells you how long the AI can be off before anything happens, though the credit itself is small | A monthly figure, a written definition of down, and a public status page |
Incidents | How fast you hear about a problem, who to contact, a written summary afterwards, and notice before changes that could alter answers | Lets you spot bad answers early and switch the AI off yourself | Updates on a status page you can subscribe to, a named contact, and a summary once it's fixed |
Resolution commitments | An agreed definition of "resolved", a test on your own tickets first, and reporting on every conversation | Tells you what you're buying before a customer sees a reply | A test period, plus reporting on every conversation |
Data and exit | What they hold, what you can export, how soon it's deleted, written confirmation, and a first term you can leave | Lets you leave with your work, on a date you chose | A stated export and deletion process, with confirmation on request |
Uptime: what counts as down, and what a credit pays
Percentages are hard to picture, so turn them into minutes. A 30-day month has 43,200 minutes, so 99.9% uptime allows about 43 minutes of downtime a month and 99.99% allows about 4.
Ask these questions before you take that headline percentage at face value:
- Is the figure measured each month, or averaged over a longer period where one bad week disappears?
- Does "down" include the AI replying with errors, or not replying at all? One public SLA only counts downtime once its error rate passes five percent (an AI that answers everyone wrongly would pass that test).
- Are planned maintenance windows excluded, and how much warning do you get before one?
- Is the credit applied automatically, or do you have to claim it? (Both of those public SLAs make you claim it, the cloud one by the end of the second billing cycle and the other within thirty days.)
Then work out what a credit is worth to you. Say you pay a vendor $2,000 a month and the AI is down for four hours, which leaves uptime at about 99.44%. On a typical 10% tier you get $200 back. If you handle 10,000 tickets a month, around 56 of them arrived during those four hours (on an even spread) with no AI to answer them.
Small credits like that usually fall well inside the vendor's profit margin, as a law firm's guidance on SaaS service levels notes, so treat them as a signal of intent. The bigger risk is a credit written as your only remedy. Another law firm's tip on service credits warns that this can take away your right to leave after repeated outages, so ask for credits to be one remedy among others.
On our side, the Enterprise plan includes a contractual 99.99% uptime SLA, which allows about 4 minutes of downtime a month.
Incidents: how fast you hear, and what happens to tickets meanwhile
An outage often goes unnoticed by your team before a customer flags it. Either tickets go unanswered because the AI stopped replying, or the AI keeps replying with something wrong.
So ask how the vendor tells you about an incident, how quickly, and who you contact while it's happening. Incident communication guidance from one large software company recommends putting every update on one status page you can subscribe to, with never more than an hour between updates. Ask for a written summary afterwards too (what happened, and what the vendor changed so it won't happen again).
Then ask what happens to incoming tickets while the AI is down, and make sure your team can switch it off without waiting on the vendor. Our AI vendor security questionnaire covers switch-off speed too, and the contract should say that your team controls the switch.
Notice of changes belongs in the same clause. Ask to be told before any change to the model or the product that could alter what customers see. Vendors also use renewals to update terms and add AI features, sometimes just by posting new terms on their website, so ask for notice of those as well.
Support from us depends on the plan. Pro has live chat support with replies within a day, Scale adds priority same-day support and a monthly video call, and Enterprise has a dedicated CSM and a monthly audit.
Resolution commitments: what to ask for and how to test it
Your procurement team may ask for a guaranteed resolution rate: write 70% into the contract and hold the vendor to it. That guarantee protects you less than it looks like it does.
The rate depends mostly on your setup: what knowledge the AI has, whether it can see order or account data (whether it can answer "where's my order" with the real status), and when your rules send a ticket to a person. So a vendor either sets the guaranteed number low enough to be safe, or attaches conditions to it. Worse, a rate target gives the vendor a reason to make reaching a person harder, because a customer who gives up trying still counts as resolved.
A prospect once showed me their AI's 92% resolution rate with some pride, and when I asked how a customer reaches a human, the answer was silence. That's why I'd ask for these four things:
- An agreed definition of resolved - for example, the customer wasn't handed to a person and didn't come back.
- A test on your own tickets - run before customers see a single reply, so you know where the rate starts.
- Reporting on every conversation - resolution, handovers and satisfaction, measured on all of them with no sampling.
- A review point you can walk away at - a date when you compare the numbers with what you were told and decide whether to carry on.
Ask where the rate will be on day one, and where it will realistically be a few months later. Quoted rates are best case, and every vendor counts "resolved" a little differently. Our resolution-rate benchmarks show how widely the field varies, so test the rate on your own tickets before you rely on it.
We count a conversation as resolved when it wasn't handed to a person, and we keep reaching a person easy so the number stays meaningful. A handover goes to your team inside the same helpdesk with a summary, so the customer doesn't have to start again. Internal Notes mode puts the AI on your live tickets as drafts your team can see and customers can't, and Insights reports resolution, handovers and AI CSAT on every conversation. The 30-day free trial includes every feature with no credit card, so you can run the whole test before you sign.
Data and exit: what you get back, what gets deleted, and how you leave
Start by asking what the vendor holds on you (the conversations, the knowledge you uploaded, and the rules and answers your team wrote). Then ask what you can export, how soon after the contract ends the rest is deleted, and whether you'll get written confirmation. Where GDPR applies, its rules for processors already require the vendor to delete or return personal data at the end of the service, at your choice. The contract should add how and when.
From what we see when teams move to us, the expensive part to rebuild is the work they put into their last AI: the rules, the custom answers and the articles they fixed along the way. Ask whether you can take that with you in a form you can use somewhere else. Our AI support migration checklist walks through what a switch involves from the other side.
A long first term with auto-renewal and a long notice period can keep you paying well after you've decided to leave. Ask for a first term you can leave after a pilot, and put the notice date in your calendar the day you sign. For GDPR and data residency detail, see our guide to AI customer service security and compliance.
With My AskAI, your data is used only to answer your tickets, and it is never used to train models or sold. Each customer's data is kept separate from every other customer's, and we're SOC 2 Type II certified and GDPR compliant. Our trust center is public, Insights exports to CSV or Sheets, and Pro and Scale can be paid month to month.
What do real AI rollouts show about these terms?
TL;DR: TravelJoy more than tripled its resolution rate by changing tools, and Edel Optics more than doubled its rate by connecting order data. A test on your own tickets shows the rate you will actually get.
These four rollouts of ours show why the resolution and exit terms deserve a large share of your negotiating time. In each one the rate was set by the tool and the setup, and two of them involved a team changing AI vendor.
TravelJoy: switching AI on the same helpdesk
TravelJoy's tickets resolved at 24% on a helpdesk's native AI and at 80% with us, after the switch. Had they been locked into a long contract with the first tool, they would have stayed on the lower number until it ran out.
Edel Optics: the rate moved when order data was connected
Edel Optics resolved 20-30% of tickets before it connected order, delivery and returns data, and 75-79% after. The lift came from setup the customer controlled, so a rate guaranteed on day one would have been set against the wrong starting point. They started in Internal Notes mode (the AI drafting replies only their team could see) before switching to direct replies.
A consumer AI-assistant app: a lower rate by design
A consumer AI-assistant app resolves 40% of its tickets with us, because its team set the escalation policy to send more conversations to people. Its AI CSAT (how satisfied customers are with the AI's replies) is 77%.
YouGarden: a vendor switch, then a month in notes mode
YouGarden moved to us from its previous AI vendor after a tender, then ran Internal Notes mode in Freshdesk for a month before letting the AI reply to customers directly. It resolves 66% of roughly 12,000 tickets a month. Ask for a testing period like that in your contract.
What should you do this week?
TL;DR: Before the order form goes back to legal, write down your position on all four sets of terms, and replace any request for a guaranteed resolution rate with a test on your own tickets and a date you can leave.
With an AI assistant doing the reading and drafting, each of these steps should take half an hour or less of your time:
- Pull every term into one page - ask an AI assistant to extract everything on uptime, credits, incidents, data and termination from the order form and terms, then read what it gives you (about 15 minutes plus reading) to see which of the four sets of terms are missing.
- Check the status page and incident history - look at the vendor's public status page and how past incidents were reported (about 10 minutes).
- Write your definition of resolved - draft it with AI, then ask the vendor to report against it on every conversation during a test on your tickets (about 30 minutes). It replaces any request for a guaranteed rate.
- Send one email about exit - ask what data is deleted when you leave, how soon, what you get back and whether you'll receive written confirmation (5 minutes). The answer can go straight into the contract.
- Put the notice date in your calendar - add the first term's notice deadline with a reminder well ahead of it (5 minutes), so the renewal doesn't slip past you.
For step 1, paste the order form and the vendor's terms into whichever AI assistant you already use, with the prompt below. Every "Not covered" line it returns is a question to send the vendor before legal sees the draft.
I'm reviewing the contract for an AI customer service agent before it goes to legal. I've pasted the order form and the vendor's terms below. Pull out everything they say under four headings: uptime, incidents, resolution, and data and exit.
Answer these questions under each heading:
- Uptime: What monthly uptime figure is promised? What counts as down, and does it include the AI replying with errors or not replying at all? Are maintenance windows excluded, and with how much warning? Is the service credit applied automatically or does it have to be claimed, and by when? Is the credit the only remedy?
- Incidents: How fast will the vendor tell us about an incident, and how? Who do we contact while it's happening? Do we get a written summary afterwards? Do we get notice before changes to the model or product that could alter answers, and before the terms change? Can our team switch the AI off without waiting for the vendor?
- Resolution: How is a resolved conversation defined? Is there a test on our own tickets before customers see a reply? What reporting do we get, and does it cover every conversation? Is there a review date where we can walk away?
- Data and exit: What data does the vendor hold? What can we export? How soon after the contract ends is the rest deleted, and do we get written confirmation? How long is the first term, does it renew automatically, and what is the notice date?
Give me a table with three columns: the question, what the documents say (quote the clause and its section number), and anything missing or unclear. Where the documents don't answer a question, write "Not covered, ask the vendor" and don't guess.
[paste the order form and terms here]If you're testing us, the 30-day free trial and Internal Notes mode are how to run step 3 before a single reply reaches a customer.
When does this advice not apply?
TL;DR: Push hardest on uptime if the AI runs overnight and at weekends on its own, and on the data terms if legal needs proof of deletion. The terms for an AI bundled into your helpdesk only change at the helpdesk renewal, and a small team on monthly billing already has its exit.
Some teams should weigh the four sets of terms differently:
- The AI covers nights or weekends alone - with nobody behind it, an outage means no support at all, so push harder on uptime, credits and how fast you hear about incidents.
- The AI is part of your helpdesk contract - its terms are written into that agreement and only move at renewal, which our guide to negotiating a Zendesk or Intercom renewal covers.
- You're a small team on a monthly plan - negotiating a custom SLA costs more time than it saves, and monthly billing plus a clean data export already give you a way out.
- Legal requires deletion confirmation and audit rights - with regulated data the data and exit terms come first.
For teams whose AI covers nights or weekends alone, our Enterprise plan includes a contractual 99.99% uptime SLA, a dedicated CSM and a monthly audit.
The takeaway
TL;DR: Check the uptime figure and credit quickly, then spend your negotiating time on incident and change notice, testing the AI on your tickets before customers see it, and an exit that returns and deletes your data.
The SLA an AI vendor hands you mostly covers uptime and credits, and an AI agent can give customers wrong answers while it's fully up. Notice of incidents and changes lets you act before more customers are affected.
TravelJoy's case study shows what a switch can do to the number. Our 30-day free trial lets you run a measured test on your tickets, with every feature on and no credit card.
FAQs
What uptime should an AI customer service vendor commit to?
99.9% a month is a common commitment in public software SLAs, and one large one uses exactly that figure. Stepping up to 99.99% cuts the allowed downtime roughly tenfold, which counts for most when your AI answers customers with nobody behind it. Our Enterprise plan includes a contractual 99.99% uptime SLA. Whatever the figure, check what counts as down and whether credits are automatic. In a 30-day month, the two figures work out like this:
Monthly uptime | Downtime allowed in a 30-day month |
99.9% | About 43 minutes |
99.99% | About 4 minutes |
Should an AI support vendor guarantee a resolution rate or accuracy level?
In my view, usually not, because the rate depends mostly on your setup and a rate target gives the vendor a reason to make reaching a person harder. Vendors also resist accuracy warranties because AI answers vary from one conversation to the next. Ask for an agreed definition of resolved, a test on your own tickets, reporting on every conversation and a review point you can walk away at.
What are service credits, and are they worth negotiating?
A service credit is money off your bill when the vendor misses its uptime commitment (usually a share of the monthly fee). One large public SLA pays 10%, 30% or 100% of the bill depending on how far uptime fell, and credits usually have to be claimed before a deadline. They deserve a little negotiating time: make them automatic, and make sure they aren't your only remedy.
What happens to my data when I end an AI customer service contract?
It depends on the contract, which is why it belongs in writing before you sign. Where GDPR applies, the vendor must delete or return personal data at the end of the service (the choice is yours). Ask what you can export, how soon the rest is deleted, and whether you'll get written confirmation.
What incident response times should the contract include?
Ask how fast the vendor tells you about an incident, how often it updates you until it's fixed, and when you get a written summary. Incident communication guidance recommends an update at least every hour during an incident, posted on a status page you can subscribe to (so nobody on your team has to keep refreshing it). Also make sure your team can switch the AI off without waiting for the vendor.
Is an AI vendor SLA different from my team's customer service SLA?
Yes, your team's customer service SLA sets the reply and resolution times you promise your customers (the usual meaning of the phrase). An AI vendor SLA is the set of commitments the vendor makes to you, covering uptime, incidents, how resolution is measured and what happens to your data when you leave.
