What is an action receipt for an AI agent? "What did the AI say, and why?" The eight fields, an example and the undo window

An action receipt is a per-message record of what an AI agent did for a customer and why. It holds eight fields: what was asked, the rule applied, the sources used, the action taken, who approved it, how it was sent and labelled, what the customer was promised, and what can still be undone. A transcript shows the words; a receipt shows the reason behind them. The reason is what people need. In a September 2026 SAS/IDC study of 2,700 decision-makers, "insufficient explanation" was reported as the top reason for overriding an AI decision, cited more than twice as often as the answer simply being wrong¹.

We publish this definition and the spec below so any owner can hold any AI tool to it, ours included.

What is an action receipt for an AI agent?#

An action receipt is created every time an AI agent sends a reply or takes an action on a customer's behalf, and it is written for the owner rather than for an engineer. Three neighbouring records are often confused with it.

• A transcript records the words exchanged. It answers "what did the AI say?" but not "why?".
• A system audit log records events in machine terms: API calls, timestamps, user IDs. It is complete and unreadable to most owners.
• A conversation summary is a paraphrase written after the fact. Its quality varies by conversation.

The receipt sits between them. It is one record per reply or action, in plain language, with the rule and the source attached. An owner should be able to read one in under a minute and know whether the agent did what the business would have done.

Why "what did the AI say, and why?" needs an answer for every message#

We decided early that every Valet reply would carry a receipt. The reasoning was a trust calculation. An owner who cannot see what an assistant said will, sensibly, stop letting it say anything, and the cost of the product is then all overhead and no work. Bluehost's 2026 survey of 350 US small-business owners found only 6% highly trust AI with their brand voice⁵. A tool asking for that trust has to show its working.

The public record shows what happens without per-message records:

• Summaries vary. A G2 reviewer of Smith.ai's AI receptionist (construction, 24 September 2025) wrote: "I wish that the summary were consistent some are very detailed and some are not."²
• Context gets lost at handoff. In an r/CRM thread titled "Best AIs for customer support? Tested a bunch." (60+ comments, about seven months old), the question that stuck was: "When AI escalates to a human, how much context actually transfers?"
• Owners end up reading logs by hand. An r/Dentists thread from late September 2026 is titled "Honest experience with an AI receptionist: I read every failed call from 15 months". One failure pattern it names: "AI said it would do it, then couldn't, and took a message".

Developers building agents that spend money have reached the same conclusion from the other side. Show HN posts in 2026 include Ledge, described as a "policy layer for AI agent payments (prevents unauthorized txns)"⁶. The common idea is a record of what the agent was allowed to do, checked at the moment it acts.

The eight fields of an action receipt#

The eight fields below are the spec. Each answers one question an owner, a customer or a tribunal could ask about a single reply. A header carries the time, the inquiry and its state.

Fields 2 and 3 carry most of the weight. A wrong answer with a correct source points at the agent. A wrong answer with a wrong source points at the document, which is the cheaper fix. Without both fields, every error looks the same.

An example action receipt#

The example below shows one receipt for one action: a held time at a small venue. It is an illustration, not a real customer.

The same record in a machine-readable form lets an agency or a developer store receipts from more than one tool in one place. Field names are suggestions; the values are the same illustration.

{
  "time": "Sun 21:11",
  "inquiry": "INQ-0001",
  "state": "Time held",
  "asked": {
    "text": "Is Saturday 14 June free for 120 guests, and what is the hire fee?",
    "channel": "website form",
    "received": "Sun 21:10"
  },
  "rule": { "topic": "Availability and published prices", "setting": "Autopilot" },
  "sources": ["Calendar", "2026 price list"],
  "action": ["reply sent", "time held: Sat 14 June"],
  "approved_by": "automatic",
  "sent_as": { "from": "bookings@", "label": "AI assistant for the business" },
  "promise": "Hold kept until Wed 18:00",
  "undo": { "reversible": ["release hold"], "until": "Wed 18:00",
            "not_reversible": ["email sent"] }
}

The undo window: which AI actions can be reversed?#

"Undo" is not one feature. It is a property of each action, and a receipt should state it per action rather than promise it in general. The table sets out the common cases for an inquiry assistant.

The first row is the uncomfortable one. Once a customer has read a price, no software can take it back. That is why the rule and source fields matter more than any undo button: they let the business stop a wrong answer from being sent twice.

How receipts help when a customer disputes what the AI said#

A receipt turns a disputed answer into a lookup. Two public cases show what the lookup would have found.

In June 2026 BMW Toronto's chatbot offered a customer CAD $27,162.79 for a used X3, against the dealer's real offer of CAD $20,000; the dealer revoked the offer and later honoured it³. The dealer's sales manager said a human employee's miscommunication led the bot to read the amount the customer still owed on the car as the amount the dealership would pay³. The number was real; it came from the wrong record. A Sources field would have shown that in one line.

In Moffatt v. Air Canada (2024 BCCRT 149), the tribunal ordered Air Canada to pay CAD $812.02 after its chatbot gave wrong information about a bereavement fare, and rejected the argument that the chatbot was a separate legal entity responsible for its own actions⁴. A receipt does not change who is responsible. It shortens the time to find out what was said, from which page, under which rule. This is not legal advice; check with counsel on whether a wrong answer binds you.

What the spec leaves out, and the open question#

The spec leaves out a confidence score. A number such as "92% confident" invites the owner to trust a figure the owner cannot check. The rule and the source can be checked. Given the SAS/IDC finding that explanation, not accuracy, drives overrides¹, we chose the checkable fields.

It also leaves out anything the agent did not touch. A receipt covers the reply and the action, not the rest of the inbox. That boundary is deliberate: Valet never reads the rest of the inbox, and a receipt standard should not require a tool to.

The open question is adoption. A receipt is only useful if buyers ask for it. Until vendors publish per-message records as a matter of course, the most useful thing an owner can do is put the eight fields into a vendor checklist, such as the questions to ask an AI vendor before it talks to your customers, and see which answers come back.

Where Valet fits#

Every Valet reply carries a Valet receipt: what was asked, the rule used, the sources used, where it was sent from and how it was labelled, with "Correct this" and "Pause topic" on each. Valet answers only from the owner's own facts, signs every reply as the business's assistant and says it is AI, and sends money, complaints and contracts to the owner with the customer told when the owner will reply. The receipt is also what makes our pricing checkable; see what counts as a booking made by Valet.

To see what your current replies would look like with a record behind each one, the free lead check takes 10–20 recent inquiries and shows what went unanswered, what stopped after one reply, and what it was worth.