What is an AI SDR? The definition, and the two rows where the label oversells
An AI SDR automates the reading and drafting parts of outbound sales development. What the term means, how it differs from an SDR and a BDR, and where it stops.
An AI SDR is software that does a sales development rep's preparation: finding accounts that fit, researching them, and drafting the outreach. The label says it replaces the role. It replaces the reading, which is most of the hours, and stops short of the two things the role is actually judged on.
An AI SDR automates account research and first-draft outreach. SDR stands for Sales Development Representative, a role that qualifies interest and books meetings rather than closing. The software covers the preparation reliably. It does not reliably decide who is not worth contacting, and it does not hold a conversation after a reply.
SDR, BDR, AI SDR
The two human titles differ by who started the conversation. An SDR works interest that already exists: a form fill, a trial, a webinar. A BDR works outbound into accounts that have shown nothing. Plenty of companies swap the definitions, and some use one title for both.
The bottom two rows are the argument. Nobody sells an AI AE, and the reason is that closing requires answering a question you did not anticipate. Those same two rows are where an AI SDR stops, which is easier to see when the roles are lined up than when the product is being demoed.
Where the term came from
The label arrived around 2023, when the underlying capability changed in one specific way: models became good enough at reading unstructured pages that the research step could be automated without producing nonsense. Before that, outbound tools automated sending and enrichment, and the research stayed manual.
Which is why the category name is slightly misleading. What got automated was not the rep. It was the reading the rep was doing at 9am before they wrote anything.
The pipeline is five jobs and vendors price all five as one. The first two are close to solved, the third depends entirely on the evidence available, and the last two are where an unattended system loses you deals rather than time.
What it does well
Reading. An account worth messaging needs someone to open the careers page, the changelog, two reviews and a LinkedIn post, and extract the two facts that matter. That is thirty-odd pages to find a sentence, and it is genuinely what a model is good at. It is also where the hour actually goes in prospecting, so compressing it is not a marginal gain.
Drafting. Fluent, structured, correctly formatted first drafts, instantly. Fluency was never the bottleneck in cold email, but not having to start from a blank box is worth something.
Consistency. It applies the same standard to account four hundred as to account one, which no tired human does at 4pm on a Thursday.
Where it stops
Deciding not to send. A tool measured on output produces output. Asked to find fifty accounts, it returns fifty, including the eleven where the honest answer was "nothing here this quarter". Restraint is the hardest behaviour to get and the most valuable, because sending to accounts with no reason attached is what burns the domain.
The reply. Demos end at send. Real outbound begins at the reply, and replies are rarely yes or no. "We looked at this in March, what changed" is a question about your roadmap, your pricing and a conversation you were not in. An agent that answers it confidently and wrongly has cost you the account, and it will sound exactly as confident as when it is right.
What to ask in a demo
Four questions, none of which are about features.
"Show me an account where it found nothing." If the tool has never returned an empty result, it does not have the concept, and every account you feed it will produce a message.
"Open the source link for that claim." Not a citation label. The actual URL, clicked, in front of you. Check the date on the page it lands on.
"What happens if I reply with a question?" Ask them to demo it on a reply that is not yes or no.
"Whose domain does this send from?" And then: what happens to that domain if the error rate is higher than expected.
The first question is the one vendors least expect, and the answer tells you more than the rest of the call.
The pricing question, briefly
| Line | Billed by | On the quote |
|---|---|---|
| Seat licence | User, per month | Yes |
| Enrichment and data | Record resolved, including failed attempts | No |
| Inboxes, domains, warmup | Mailbox, plus the domain you risk | No |
| Human review | The hour, from someone already busy | No |
The five questions worth asking before buying one are here, along with a two-week test that answers them better than four vendor calls.
A definition worth using
If you want one sentence for a deck: an AI SDR is a research and drafting system with a sales title. That framing predicts its behaviour correctly. The alternative framing, a rep that does not sleep, predicts it will handle a reply, and it will not.
Who should not buy one
Anyone whose outbound does not already work at ten messages a week. These multiply a process. A process producing nothing, multiplied, produces nothing across four domains.
Anyone under roughly fifty target accounts. At that size the research is a morning a week and the tool is overhead you now have to review.
Anyone who cannot spare the review time. The review is not optional. A tool bought to save time that instead creates a daily reading task gets cancelled in month three, usually after the domain has taken some damage.
Revtive sits deliberately in the first half of that pipeline: it researches and drafts, cites a source for every signal, and does not send on its own. The split follows the two rows above rather than the market's preference for selling the whole pipeline as one thing.