# AI SDR in Outreach: What AI Does and What People Do

An AI SDR should support B2B outreach, not run it alone. At OT9, AI researches companies, drafts email personalization and sorts incoming replies; people define the ICP and offer, approve every message, and handle qualification and conversations. This keeps quality controlled at scale: 5.93% of companies reached replied across our campaigns.

**Figures:** 5.93% — of companies reached replied across our campaigns; 48,100 — companies replied across the campaign period; 6,500 — clear positive replies: requests for details, a proposal or a meeting

## What AI agents do in our campaigns

We use AI for three preparatory tasks: company research, first drafts of personalization and incoming-reply triage. These are areas where a machine can accelerate routine work while a person reviews the output before it affects a prospect.

- **Company research.** The agent reviews public information and prepares a fact sheet on what a company does, its scale and relevant recent changes. It supports the work behind [lead list building](/en/services/lead-list-building/).
- **Personalization drafts.** Based on verified facts, the model proposes an opening paragraph and a relevant reason to contact the company. An editor removes generic language, checks the facts and corrects the tone.
- **Reply triage.** Incoming messages are classified as interest, question, rejection, wrong contact or unsubscribe request. The manager receives a prioritised queue instead of a chronological inbox.

In market terminology, this setup is an AI SDR: an agent that takes routine work from a sales-development specialist. We use it to strengthen the operator, not replace the person accountable for the outreach.

## What remains with people

A machine does not decide whom you should sell to or what you should offer. Those decisions remain with the people responsible for the campaign.

- **ICP and offer hypothesis.** Together with you, a strategist defines the target customer, offer and lead criteria during the brief.
- **Final email copy.** AI can draft personalization, but a person reviews and approves the message sent to the recipient.
- **Non-standard replies.** Objections, commercial questions and negotiation require a manager from the [reply-handling](/en/services/reply-handling/) team, not a bot.
- **Meeting decisions.** A positive reply is qualified and passed to your sales team through a manual check.
- **Quality control.** Research cards and drafts are sampled and reviewed. If quality drops, the agent is adjusted before further work continues.

## Why a fully autonomous AI SDR still falls short

Services that promise an agent will find prospects, write to them and sell without oversight lose to a machine-plus-person setup in four areas.

- **Facts.** A model can confidently use the wrong news item, role or location. One inaccurate email can permanently damage trust with a company.
- **Repetition.** Large volumes of messages from one generative pattern begin to sound alike. Both recipients and spam filters recognise formulaic copy.
- **Conversation.** An autonomous agent may handle an opening message, but later replies require negotiation context and judgement.
- **Domain reputation.** Unsupervised automation can damage deliverability. Restoring a domain's reputation takes time and careful work.

We tested autonomous operation on our own infrastructure before offering this setup to clients. Our conclusion: AI is effective at removing draft work, but giving it the final word before a message is sent costs quality and replies.

For the practical boundary, see our comparison resources in [B2B outreach comparisons](/en/comparisons/).

## How the service works

1. **Brief and ICP.** We define the customer profile, offer and lead criteria with you.
2. **List building.** We collect and validate companies that fit the ICP, while AI assists with research on priority accounts.
3. **Email setup.** Outreach email infrastructure is prepared separately and deliverability is established before campaign activity begins.
4. **Sequences.** An editor and the model prepare segmented email sequences: people own the structure and offer, AI drafts possible openers, and people make the final edits.
5. **Launch.** Campaigns go out in controlled waves by segment, with monitoring and adjustment throughout.
6. **Reply handling.** AI sorts replies for the manager; standard questions follow agreed guidance and the rest are handled personally.
7. **Reporting.** You receive regular funnel reporting on companies reached, replies, clear positive replies and meetings, with ongoing adjustments to segments and copy.

A pilot normally takes four to six weeks from the brief to the first qualified positive replies. The campaign can then expand segment by segment.

## What determines the result

- **ICP accuracy.** The narrower and more honest the profile, the better the campaign can perform. A vague target such as every company in a country wastes both list capacity and budget.
- **Offer strength.** AI can accelerate research, but it cannot invent a reason to buy. Personalization cannot rescue a weak offer.
- **Market size.** Where a segment contains only a small number of target accounts, a manual account-by-account approach may be more economical than AI-assisted research.
- **Your response speed.** A lead cools within hours. If a positive reply waits a week for your sales team, the problem is not the channel.

We model unit economics against your deal size and conversion assumptions before launch, using your numbers rather than promises.

## When this setup is not for you

We will say so directly if the service is a poor fit. We do not take on work where:

- you need complete autonomy with no people involved;
- the niche contains only a small, tightly defined account list where manual research is more efficient;
- there is no clear product or offer yet;
- you need a guaranteed number of leads by a fixed near-term date. We work in controlled waves and report the funnel, not a number outside our control.

## How we measure results and set the price

We measure the funnel, not abstract reach: how many companies received a message, replied, gave a clear positive reply and reached a meeting. The key checkpoint is a clear positive reply: a request for details, a proposal or a meeting.

Across our campaigns, 3,224,000 emails have been sent to 811,200 companies. 48,100 companies replied, equal to 5.93% of companies reached, and 6,500 gave a clear positive reply. 97.7% of addresses accepted the email, with a 2.3% bounce rate. These figures describe the mechanics of our work, not a promise for your niche.

Pricing depends on channels, list volume, the depth of personalization and whether we manage replies end to end. See [pricing](/en/pricing/) for the structure, and [guarantees](/en/guarantees/) for what counts as a lead and what we guarantee.

## Frequently asked questions

**Will an AI SDR replace my sales team?**

No. The agent removes draft work: company research, first personalization options and reply sorting. People conduct negotiations, qualify opportunities and run meetings. That distinction matters in B2B sales with mid-market and enterprise deal sizes.

**Can I buy a tool and send AI-written emails without an agency?**

Technically, yes. The risks are inaccurate facts, copy that becomes repetitive, and automation that harms email deliverability. A person in the review loop is usually less expensive than repairing those consequences later.

**How does AI personalize an email for a specific company?**

The agent gathers facts from public sources and drafts an opening paragraph that links a real company context to your offer. An editor verifies the facts and revises the draft before anything is sent. No unreviewed draft goes to a recipient.

**Will the recipient know that AI wrote the email?**

An unedited draft often gives itself away through generic phrasing and irrelevant compliments. After human editing and a connection to a real, verified company fact, the message reads as a concise business email from someone who did the homework.

**What happens if the agent gets company facts wrong?**

That is why the process has two levels of control: every sendable draft is reviewed and research output is checked in samples. If the error rate in the sample rises, the agent is adjusted before further work proceeds. Only verified material is sent.

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Source: https://ot9.ru/en/services/ai-in-outreach/ · OT9 (KAP Group) · updated 2026-08-10