Which conversation intelligence vendors state whether your calls train models for other customers?

The distinction between "we do not" and "you can turn it off" is the whole question, and only one of those survives a change of product manager.

An opt out that only applies going forward leaves everything recorded during the pilot inside the boundary you were trying to stay outside of.

Deletion that leaves the embedding behind is not deletion. Ask specifically about derived artifacts, because retention policies usually describe the source file.

The vendor may make you a firm commitment that its model provider does not. Ask for the chain, and ask whether the commitment travels down it.

Human access is the part almost nobody publishes. A vendor with real controls can describe them in a sentence.

A support article can be edited on a Tuesday afternoon. This is the test that separates a published position from a commitment.

Which conversation intelligence vendors state whether your calls train models for other customers?

35 of the 68 conversation intelligence vendors in the index document their AI safety and data stewardship posture at a standard a buyer can check, 51 percent. 13 are graded at the top of the scale: Bluedot, Demodesk, Gong, Krisp, MeetGeek, Read AI, Revenue.io, RingCentral AI Conversation Expert, Salesloft, Scratchpad, Seismic Enablement Cloud, tl;dv, Zoom Revenue Accelerator. A further 22 publish a position that is checkable without being complete: Attention, Claap, Dialpad, Fireflies.ai, FrontSpin, Granola, Highspot, Jiminny, Klenty, Koncert, Lusha, MakeSales, Mindtickle, Numoloo, OnePgr, Opine AI Presales Platform, Otter.ai, Outdoo AI, Outreach, Quantified AI, Sybill, Tuvis. The remaining 33 say something without saying enough, and notably 1 do not address it at all. That last detail is the shape of this category: nobody ignores the question, and most answer it with a sentence about security rather than a statement about the boundary. A recorded sales call contains your pricing, your discounting behavior, your objection handling and your customer's own words. Whether that content can improve a model another company uses is a contractual question with a one line answer, and the majority of this category has not published the line.

What exactly should a vendor commit to here?

Four things, and they are separable. First, whether customer content is used to train or fine tune models that serve any customer other than you, stated as a default rather than as an option. Second, if there is an opt out, whether it is on by default, where it is configured, and whether it covers content already ingested. Third, retention: how long recordings, transcripts and derived embeddings are kept, and whether deletion of a recording deletes what was derived from it. Fourth, who inside the vendor can access customer content, under what controls, and whether subprocessors including model providers receive it. A vendor can be excellent on security certifications and still have published nothing about any of the four, which is why this axis is graded separately from Security Certifications and Trust Center.

Is this only a conversation intelligence problem?

No, but it is sharpest there. Across all 406 vendors in the index, 111 document this axis at a checkable standard, 27 percent, and 33 do not address it at all. Revenue intelligence platforms manage 25 of 56, 45 percent, and AI SDR agents 22 of 86, 26 percent, with 13 of the agents silent on it entirely. Conversation intelligence documents it best of the three, which is the honest reading, and it is also the category holding the most sensitive material. A category that ingests recorded human conversation and is best in class at 51 percent is not a category with a solved problem.

What does a grade on AI Safety and Data Stewardship cover?

The whole axis and the whole vendor, which is worth stating plainly because a reader arriving from a training boundary question will want it to mean only that. The axis bundles the cross customer training boundary, retention and deletion of customer content, and the controls governing model and human access to it. An A means all of that is addressed in public material at a standard a buyer could hold a vendor to; a B means it is addressed with a gap. A grade also belongs to a vendor rather than to one of its products, so on a vendor listed in more than one category the grade may have been earned on a different product line. As everywhere in this index, a grade records what has been published: a low grade means the public record is thin rather than that the practice is bad, and many vendors will answer in a contract what they have not answered on their site.

How does the GTM Tech Index grade this?

As one of 17 capability axes applied identically to all 406 vendors, graded from public artifacts with a source basis and verification date recorded on every vendor profile. Grades are never aggregated into a composite score. Category membership is primary or secondary, so a vendor appears in a lane if it sells into it, which is why these counts run larger than the primary only counts on the features page. This page is an editorial reference and not legal advice.