Every AI SDR vendor runs the same slide. An SDR costs $85,000 a year. Our product costs $499 a month. The arithmetic does the rest.
The arithmetic is real and the comparison is not, because it prices an AI SDR as a replacement for a person when it is actually a replacement for part of a person’s week. Nobody who has run one at volume thinks otherwise.
Here is the version with the missing lines in it.
What a human SDR costs
Fully loaded, in the US, for a mid-level SDR:
| Line | Annual |
|---|---|
| Base salary | $55,000–$70,000 |
| Commission at target | $15,000–$25,000 |
| Payroll tax and benefits | $12,000–$18,000 |
| Tooling and data | $3,000–$6,000 |
| Management time | $8,000–$12,000 |
| Total | $93,000–$131,000 |
Call it $100,000, or roughly $8,300 a month. Outside the US this falls considerably; in parts of Europe and in India the same role runs a third to a half of that, which changes the whole calculation and is worth noting because most AI SDR comparisons are written as though everyone hires in San Francisco.
Then the parts that are not salary. Ramp is three to five months before a new SDR is productive. Median SDR tenure in B2B sits somewhere around 18 months, so you ramp roughly every year and a half. And capacity is fixed: one person does one person’s volume regardless of how good your list is.
What an AI SDR costs, fully loaded
The headline is the software. It is not the total.
| Line | Monthly |
|---|---|
| AI SDR software | $300–$900 |
| Lead data | $100–$300 |
| Email infrastructure | $150–$400 |
| AI credits or per-action fees | $50–$200 |
| Human oversight | The variable that matters |
| Total before the human | $600–$1,800 |
Against $8,300 that still looks decisive, and at low volume it is. The line to think hard about is the last one.
An AI SDR sources, writes and sends. It does not decide which market to enter, judge whether a half-interested reply is worth a call, handle a prospect who asks something outside its training, or notice that the messaging has stopped working because the market moved. Somebody does those things.
At modest volume that is a few hours a week, and the economics are overwhelming. At real volume it is a meaningful part of a job, and the honest figure is software plus a fraction of a person, not software alone.
What the tools genuinely do well
Worth being specific, because the category attracts both overselling and reflexive dismissal.
Volume without linear cost. Doubling output does not mean doubling headcount. This is the real advantage and it is substantial.
Consistency. Follow-ups go out on schedule every time. Human SDRs drop follow-ups, and a large share of replies come from touches three through six.
Speed of response. A reply answered in four minutes converts better than one answered the next morning. Machines are simply better at this.
First-draft personalisation at scale. Reading a prospect’s recent activity and producing a relevant opener across thousands of leads is work no human does well at volume.
Never having a bad week. Output does not dip because of a difficult quarter or a resignation.
What they still get wrong
Judgement on ambiguous replies. “Interesting, but we just signed with someone else” could be a dead end or a twelve-month opportunity. Models tend to treat it as one thing consistently, and which thing depends on the prompt rather than the situation.
Anything outside the brief. A prospect asks a pointed question about security posture or contract terms. The right move is to stop and hand off. Not every system does.
Compounding sameness. Every team using the same models on the same prompts produces convergent output. The personalisation that worked in 2024 reads as automated in 2026 precisely because it worked.
Knowing when to stop. A human notices a segment is not responding after forty sends. A machine happily completes ten thousand.
Deliverability judgement. Most “the AI SDR didn’t work” stories are deliverability stories. The tool sent perfectly good email into the spam folder at scale, and nobody was watching the placement.
The comparison that is actually useful
Not either-or. The question is which parts of the job go where.
| Task | Better handled by |
|---|---|
| List building against defined criteria | AI |
| Deciding the criteria | Human |
| First-draft sequence copy | AI |
| Approving what sends | Human |
| Sending and follow-up scheduling | AI |
| Categorising replies | AI |
| Handling an ambiguous reply | Human |
| Booking a straightforward meeting | AI |
| Qualifying a complex opportunity | Human |
| Watching deliverability | Both, with alerting |
| Noticing the messaging has gone stale | Human |
Teams that get good results run something like a 1:3 ratio, where one person oversees roughly the output of three traditional SDRs. That is a genuine productivity gain and it is a different claim from replacement.
Where each one wins
AI SDR wins when the motion is high-volume and repeatable, the ICP is broad, the product explains itself in an email, deal sizes are small enough that per-lead human attention cannot be justified, or you need to test several markets quickly without hiring.
A human SDR wins when deals are large enough that one lost opportunity outweighs a year of software cost, the sale is technical or consultative, you sell into a small named account list where every touch matters, or the buying process needs relationship-building rather than sequencing.
Both is where most teams past a certain size land: AI handles the top of the funnel at volume, humans take over the moment somebody shows genuine interest. The handoff rule is the thing to design carefully, because it is where most of the value and most of the damage sits.
The question to ask a vendor
Not “does it book meetings”. Ask this instead: what happens when it does not know what to do?
Good answers describe escalation. It flags the reply, routes it to a person, pauses the sequence, waits. Bad answers describe confidence. It handles everything, it learns, it adapts.
A system that never hands off is not more autonomous. It is less honest about the boundary, and you will find the boundary anyway, usually in a thread with a prospect you wanted.
The short version
An AI SDR fully loaded costs $600 to $1,800 a month plus a fraction of a person’s time. A human SDR costs around $8,300 a month in the US, considerably less elsewhere, with three to five months of ramp and fixed capacity.
The gap is real and it favours AI for high-volume, broad-ICP, self-explanatory products. It narrows fast when deals are large, sales are consultative, or the account list is small enough that every touch matters.
And it is not a replacement. It is a ratio change: one person overseeing the output of three. Budget for the person, choose the tool on how well it hands off, and watch your deliverability, because that is what actually kills these programmes.
Next: AI reply agents compared, or agency versus in-house, priced.
Frequently asked questions
How much does an AI SDR cost?
Software alone runs roughly $300 to $900 a month. Fully loaded with lead data, email infrastructure and AI credits, expect $600 to $1,800, plus the time of whoever oversees it.
Can an AI SDR replace a human SDR?
Not entirely. It replaces the repeatable parts — sourcing, drafting, sending, follow-up scheduling, reply categorisation — and leaves judgement, ambiguous replies and complex qualification with a person. Teams typically see one person covering roughly the output of three.
Is an AI SDR worth it for a small team?
Often yes, because the alternative is that outbound competes with everything else on a founder’s calendar and quietly loses. At small volume the oversight burden is a few hours a week.
What do AI SDRs get wrong most often?
Deliverability is the biggest one; the tool sends good email into spam at scale and nobody notices. After that, judgement on ambiguous replies and failing to hand off questions outside the brief.
AI SDR or an outbound agency?
An agency buys experience and speed with a three to six month horizon. An AI SDR buys capacity you own. If outbound is a permanent function, the tool plus a person is usually cheaper within a year.