Quick answerStructure customer-facing AI agent SLA terms around two separate commitments: availability (the agent responds within expected time and is not down) and accuracy (the agent's answers meet a defined quality bar on defined categories of question). Offer service credits, not cash refunds, tied to measurable thresholds you can actually monitor, and explicitly scope which types of answers the accuracy commitment covers, since guaranteeing accuracy on open-ended conversation is not realistic.
This is the mirror image of vendor SLA negotiation, not the same topic
If your company buys an AI agent capability from a vendor, you negotiate SLA terms as the buyer, covered in how to negotiate SLAs and support terms in an AI agent vendor contract. This post is the reverse direction: your company built or deployed an AI agent that your own customers now depend on, and they are starting to ask what commitments you are willing to put in writing about its performance. The negotiating leverage, the metrics that matter, and the credit structures look different when you are the one making the promise instead of extracting one.
Separate availability from accuracy in the contract language
These are genuinely different failure modes and should never be bundled into a single SLA metric. Availability is straightforward to define and monitor: the agent is reachable and responding within an acceptable latency window some percentage of the time, measured the same way any other software uptime commitment is measured.
Accuracy is harder, and vague accuracy language is a trap for both sides. "The agent will provide accurate information" is not a testable commitment. A workable version scopes accuracy to specific, monitorable categories: factual claims sourced directly from your systems (account status, pricing, order information) rather than open-ended advice or judgment calls. Commit to a defined error rate on those scoped categories, measured against your own production quality metrics, not against every possible thing the agent might say in conversation.
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Structure credits, not refunds, and tie them to real thresholds
Service credits applied against future billing are the standard structure for a reason: they are lower risk for you than cash refunds, and they still give the customer a meaningful remedy. Tier the credit to the severity of the miss rather than an all-or-nothing trigger, similar to how conventional software uptime SLAs scale credits by how far below the threshold actual performance fell.
Before committing to any specific number, confirm you can actually measure it in production. A commitment you cannot monitor is a liability with no corresponding operational discipline behind it, and it will surface exactly when a customer disputes a specific incident and asks for the data.
What not to promise
Do not offer an SLA that implies zero errors, ever, on any category of question. It will be violated, and a violated absolute promise is worse for trust than a realistic scoped one that occasionally triggers a modest, expected credit. It is also worth thinking about how these terms interact with your business insurance coverage for AI agent mistakes, since a contractual SLA credit and an insurance claim are different remedies for different severities of failure and your terms should not accidentally promise more than either mechanism can actually deliver.
FAQ
Should the SLA cover every type of answer the agent gives?
No. Scope the accuracy commitment to answers sourced from your own systems where you can define and measure correctness. Open-ended conversational responses are not a good fit for a hard accuracy guarantee.
Are service credits enough, or should enterprise customers get more?
For large or strategic accounts, some companies negotiate custom terms beyond standard credits, but the baseline offering to all customers should stay simple and consistently enforceable rather than ad hoc.
How does this interact with the vendor SLA if we resell someone else's AI agent?
Your customer-facing commitment should never be more generous than what your own upstream vendor commits to you, or you are absorbing risk your vendor contract does not actually cover.