--- title: "Find Clients for Your Recruiting Agency Using AI" description: "Use AI agents like Claude and ChatGPT to find, target, and win new clients for your staffing agency. Includes prompts, connected workflows, and templates." url: "https://www.leonar.app/blog/find-clients-recruiting-agency-ai-agents/" lang: "en" alternates: fr: "https://www.leonar.app/fr/blog/find-clients-recruiting-agency-ai-agents/" de: "https://www.leonar.app/de/blog/find-clients-recruiting-agency-ai-agents/" image: "https://www.leonar.app/og/blog/find-clients-recruiting-agency-ai-agents-en.png" tokens: 8196 --- 1. [Home](https://www.leonar.app/) 2. [Blog](https://www.leonar.app/blog/) 3. [Staffing](https://www.leonar.app/blog/category/staffing/) 4. Find Clients for Your Recruiting Agency Using AI Agents Staffing March 10, 2026 17 min read # Find Clients for Your Recruiting Agency Using AI Agents Use AI agents like Claude and ChatGPT to find, target, and win new clients for your staffing agency. Includes prompts, connected workflows, and templates. [![Pierre-Alexis Ardon](https://www.leonar.app/_astro/pierre-alexis-ardon.ByBiMn-t_1eJ10c.webp)](https://www.leonar.app/authors/pierre-alexis-ardon/) [Pierre-Alexis Ardon](https://www.leonar.app/authors/pierre-alexis-ardon/) Co-founder Updated July 23, 2026 ![Recruiting agency using AI agents to find and win new clients through automated targeting and outreach](https://www.leonar.app/_astro/find-clients-recruiting-agency-ai-agents.BH5rn2Qr_1HdCU7.webp) Ready to take action? Discover Leonar in a few minutes. Summarize with AI Choose an AI [ChatGPT](https://chat.openai.com/?q=Summarize%20this%20article%20about%20recruiting%20from%20Leonar%3A%20) [Perplexity](https://www.perplexity.ai/search/new?q=Summarize%20this%20article%20about%20recruiting%20from%20Leonar%3A%20) [Claude](https://claude.ai/new?q=Summarize%20this%20article%20about%20recruiting%20from%20Leonar%3A%20) [Mistral](https://chat.mistral.ai/chat?q=Summarize%20this%20article%20about%20recruiting%20from%20Leonar%3A%20) Table of contents - [Why traditional business development stalls for recruiting agencies](#why-traditional-business-development-stalls-for-recruiting-agencies) - [What AI agents actually do for agency business development](#what-ai-agents-actually-do-for-agency-business-development) - [Five AI-powered workflows to win new clients](#five-ai-powered-workflows-to-win-new-clients) - [1\. Mine job postings to spot companies that need you right now](#1-mine-job-postings-to-spot-companies-that-need-you-right-now) - [2\. Build detailed ideal client profiles with AI research](#2-build-detailed-ideal-client-profiles-with-ai-research) - [3\. Generate personalized outreach that doesn’t sound like a template](#3-generate-personalized-outreach-that-doesnt-sound-like-a-template) - [4\. Automate follow-up and nurturing sequences](#4-automate-follow-up-and-nurturing-sequences) - [5\. Score and prioritize your deal pipeline with AI analysis](#5-score-and-prioritize-your-deal-pipeline-with-ai-analysis) - [Two 2026 plays most agencies miss: AI variables and voice notes](#two-2026-plays-most-agencies-miss-ai-variables-and-voice-notes) - [Give every prospect a unique first line with AI variables](#give-every-prospect-a-unique-first-line-with-ai-variables) - [Stand out with a LinkedIn voice note](#stand-out-with-a-linkedin-voice-note) - [How to connect Claude or ChatGPT to your recruiting CRM](#how-to-connect-claude-or-chatgpt-to-your-recruiting-crm) - [The targeting workflow: from a researched company list to an enriched contact](#the-targeting-workflow-from-a-researched-company-list-to-an-enriched-contact) - [The messaging workflow: AI-drafted outreach sent through real channels](#the-messaging-workflow-ai-drafted-outreach-sent-through-real-channels) - [The nurturing workflow: automated pipeline monitoring and re-engagement](#the-nurturing-workflow-automated-pipeline-monitoring-and-re-engagement) - [Prompts and templates you can use today](#prompts-and-templates-you-can-use-today) - [Prompt: identify high-potential target companies](#prompt-identify-high-potential-target-companies) - [Template: personalized agency introduction email](#template-personalized-agency-introduction-email) - [Prompt: draft a nurturing sequence for stale deals](#prompt-draft-a-nurturing-sequence-for-stale-deals) - [Common mistakes when using AI for agency business development](#common-mistakes-when-using-ai-for-agency-business-development) Most recruiting agencies approach [business development](https://www.leonar.app/blog/recruitment-business-development/) the same way they did ten years ago. [Cold calls](https://www.leonar.app/blog/recruitment-cold-calling-scripts/), LinkedIn connection requests, [marketing their most placeable candidate](https://www.leonar.app/blog/most-placeable-candidate/), and the occasional referral. It works, but it doesn’t scale, and it burns out your team. Our guide to [getting clients for a staffing agency](https://www.leonar.app/blog/get-client-staffing-agencies/) covers the foundational methods, while this article adds AI workflows. Since a repeatable BD engine is exactly what lets a firm move up a stage, this fits into the bigger picture of [how to grow a recruitment agency](https://www.leonar.app/blog/how-to-grow-a-recruitment-agency/). Meanwhile, AI agents (tools like Claude, ChatGPT, and purpose-built recruiting AI) have gotten remarkably good at research, writing, and workflow automation. They are also moving from experiments into recruiting teams’ day-to-day plans. But nearly every guide about AI in recruiting focuses on the candidate side: sourcing talent, screening resumes, scheduling interviews. Almost nobody talks about using AI agents for the other half of the business: **finding and winning clients.** This guide fills that gap. You’ll learn five concrete workflows for using AI agents to identify target companies, craft personalized outreach, and nurture deals through your pipeline. Then we cover two newer plays most agencies miss: AI-generated sequence variables that write a unique line for every prospect, and LinkedIn voice notes you can send from your desktop or automate inside a sequence. You’ll also see how connecting an AI to your recruiting CRM through the Model Context Protocol (MCP) turns these workflows from manual prompt-and-paste sessions into systems the AI can run for you. ## Why traditional business development stalls for recruiting agencies The math is brutal. According to staffing industry benchmarks, the average recruiter-turned-BD-rep makes 40 to 60 outreach attempts per week. Response rates on cold emails hover around 5 to 8%. That means weeks of effort to generate a handful of conversations, most of which go nowhere. Three structural problems make this worse: **Generic messaging kills response rates.** When you send the same “We help companies hire top talent” pitch to 50 different prospects, you sound like every other agency in their inbox. Decision-makers at companies receiving 10+ agency pitches per month can spot a template instantly. **Research takes longer than outreach.** Before you can write a personalized message, you need to understand the company’s hiring needs, growth stage, tech stack, team structure, and recent job postings. That research often takes 15 to 20 minutes per prospect, which means your team spends 80% of BD time on research and 20% on actual selling. **Follow-up falls through the cracks.** Staffing industry data shows that 80% of deals require five or more touchpoints. But most agency owners track follow-ups in spreadsheets or their heads. Deals go cold not because the prospect wasn’t interested, but because nobody followed up at the right time. AI agents solve all three problems. They research faster than any human, they generate personalized copy in seconds, and they never forget a follow-up. ## What AI agents actually do for agency business development Before diving into workflows, let’s be precise about what “AI agent” means here. There are two layers: **Conversational AI (Claude, ChatGPT, Gemini).** These are general-purpose models you can prompt with instructions. They’re excellent at research synthesis, copywriting, data analysis, and reasoning. You give them context about a prospect, and they produce a personalized email in 10 seconds. But on their own, they can’t pull live data from your CRM or send messages on your behalf. **AI agents connected to your tools.** When you connect a conversational AI to your recruiting CRM through a structured connection or protocol like MCP (Model Context Protocol), the AI gains the ability to search your database, look up LinkedIn profiles, enrich contacts with emails, enroll prospects in outreach sequences, and manage deals. This is where the real leverage lives: the AI doesn’t just draft the email, it finds the prospect, enriches their contact info, sends the message, and tracks the deal. The workflows below start with what you can do today using just a chat interface, then show how connecting to your CRM unlocks fuller automation. ## Five AI-powered workflows to win new clients ### 1\. Mine job postings to spot companies that need you right now The strongest signal that a company needs a recruiting agency is that they’re actively hiring and struggling to fill roles. Job postings that have been open for 30+ days, roles reposted multiple times, or companies with 20+ open positions relative to their team size are all high-intent signals. Here’s how an AI agent handles this. You prompt Claude or ChatGPT with something like: > “I run a staffing agency specializing in software engineering roles in the fintech sector. Analyze these 15 LinkedIn job postings I found and rank them by urgency. Look for signals like: posting age over 30 days, multiple similar roles at the same company, senior roles posted alongside junior ones (suggesting team build-outs), and mentions of ‘immediate start’ or ‘urgent hire.’ For the top 5, draft a one-paragraph summary of why this company likely needs outside recruiting help.” The AI returns a prioritized list with context you’d never have time to compile manually. Instead of blasting 50 companies, you approach 5 with a message that references their specific hiring challenges. The same signals sit at the heart of any lead engine, whether or not you use AI: our guide to [lead generation for staffing agencies](https://www.leonar.app/blog/lead-generation-staffing-agencies/) breaks down each lead source and how to buy versus build your list. If you use a recruiting CRM with a [connected LinkedIn job search workflow](https://www.leonar.app/blog/connect-ai-agents-recruiting-stack-mcp-api/), this gets even more powerful. The AI can search LinkedIn automatically for job postings matching your niche, filter by location and company size, and surface only the highest-intent prospects, all without you opening a browser tab. ### 2\. Build detailed ideal client profiles with AI research Most agencies define their ideal client profile (ICP) in vague terms: “mid-size tech companies in New York that hire engineers.” AI agents can make this dramatically more specific. Feed your AI the profiles of your five best existing clients and prompt: > “Analyze these five companies. Identify the patterns: what industry sub-segments are they in, what’s their headcount range, how many open roles do they typically have, what job titles do they hire for most, what ATS or HR tools do they use, and what growth signals appeared before they became our clients (funding rounds, office expansions, leadership hires)? Build a detailed ICP I can use to find similar companies.” The AI will find patterns you missed. Maybe your best clients all raised Series B funding 6 to 12 months before engaging you. Maybe they all have between 100 and 300 employees with no internal recruiting team. These signals become your targeting criteria. From there, ask the AI to generate a list of companies matching the profile. If it’s connected to your CRM and can [search LinkedIn companies](https://www.leonar.app/blog/ai-recruiting-tools/), it can pull live data and cross-reference it against your existing client list to avoid duplicates. ### 3\. Generate personalized outreach that doesn’t sound like a template This is where AI agents deliver the most immediate ROI. Instead of sending the same agency pitch to every prospect, you give the AI context about each company and ask it to write a message that references their specific situation. The key is quality of input. A prompt like “write an email to a prospect” produces garbage. A prompt like this produces gold: > “Write a cold email from me (Sarah, founder of TechTalent Partners, a staffing agency specializing in backend engineering for fintech companies) to James Miller, VP of Engineering at PayFlow (Series B fintech, 180 employees, 12 open engineering roles, headquartered in Austin). PayFlow just raised $40M and posted 8 new roles in the past two weeks. Keep it under 120 words. Reference their growth specifically. Don’t pitch our services directly. Instead, offer a free market salary benchmark for their open roles. Sign off with a soft ask for a 15-minute call.” That level of personalization used to take 20 minutes of research and writing per prospect. With AI, it takes 30 seconds, and the output is often better because the AI follows the structure perfectly every time. For agencies sending outreach at scale, tools that support [automated LinkedIn messaging](https://www.leonar.app/blog/linkedin-automated-messaging/) and multi-channel sequences become essential. The AI drafts the message, and the CRM handles delivery across email, LinkedIn, and WhatsApp. The newest twist is AI sequence variables. Instead of one static template, you drop a placeholder like `{{ai_icebreaker}}` into a step and let the AI write a unique opener for each prospect at send time. You write one prompt once, and every contact in the campaign gets a personalized first line. We cover exactly how to set that up later in this guide. ### 4\. Automate follow-up and nurturing sequences Here’s a stat that should make every agency owner uncomfortable: Internal CRM benchmark data shows that 60% of deals in recruiting CRMs haven’t been touched in over 14 days. These aren’t dead leads. They’re prospects who expressed interest but fell off your radar because your team got busy filling existing roles. AI agents excel at nurturing because they never forget and they never get busy. A connected AI agent can: - Scan your deal pipeline daily for prospects that haven’t received a touchpoint in 7+ days - Draft a contextual follow-up based on the last conversation (not a generic “just checking in”) - Adjust the tone and offer based on the deal stage (early stage gets thought leadership content, late stage gets case studies and ROI data) - Flag deals that have gone cold for a human review The follow-up message an AI drafts for a prospect who asked about pricing two weeks ago looks very different from the one it drafts for a prospect who attended your webinar last month. That contextual awareness is what separates AI nurturing from basic drip campaigns. ### 5\. Score and prioritize your deal pipeline with AI analysis Most agencies treat every prospect the same. But AI agents can analyze your pipeline and tell you where to focus your time. Feed your CRM data to an AI and prompt: > “Here are my 35 open deals with their stage, last activity date, deal value, and notes. Based on engagement signals (response speed, number of touchpoints, questions asked), rank them by likelihood to close this month. For the top 10, suggest a specific next action. For the bottom 10, recommend whether to nurture, pause, or archive.” This turns a messy pipeline into an actionable priority list. Combined with the [deal tracking capabilities of a recruiting CRM](https://www.leonar.app/blog/best-recruitment-crm/), the AI can access this data directly and generate the analysis on demand. ## Two 2026 plays most agencies miss: AI variables and voice notes Two features rolled out recently that change how agency outreach feels on the receiving end. Both are worth setting up before your competitors do. ### Give every prospect a unique first line with AI variables Sending the same template to 200 companies is the fastest way to get ignored. AI sequence variables fix that without asking you to write 200 emails. In the sequence editor you add a placeholder like `{{ai_icebreaker}}` to a step, then write one short instruction prompt for it, for example: “Open with one specific observation based on the prospect’s role, company, and industry, in one sentence, no flattery.” When the sequence sends, Leonar generates that line for each recipient from their profile data (name, title, company, industry), so the opener can vary by prospect. You set a fallback value for the variable too, which means if generation ever times out, the message still goes out cleanly instead of showing a broken `{{ }}` token. You write the prompt once and the whole campaign feels handcrafted. It is the same idea recruiters already use to [source candidates with connected AI agents](https://www.leonar.app/blog/source-candidates-ai-agents-workflow/), turned toward winning clients instead. ### Stand out with a LinkedIn voice note Almost nobody sends voice notes for business development, which is exactly why they land. A ten-second voice message that says the prospect’s name and references their open roles cuts through a text-only inbox. LinkedIn only lets you record voice messages from its mobile app. Leonar lets you record and send them straight from your desktop inbox, and even automate them inside a sequence. For a high-value prospect, record a personal note in the inbox composer (recordings are capped at two minutes). For volume, add a LinkedIn voice step to a sequence and it sends automatically from your connected LinkedIn account. Prefer to record each one yourself? Run the same step as a manual task and record it at send time. ## How to connect Claude or ChatGPT to your recruiting CRM This is where things get interesting for agencies that want to move beyond copy-pasting between ChatGPT and their CRM. When you connect an AI to your recruiting workspace, you create a system where the AI can autonomously execute entire business development workflows. The cleanest way to do this today is the Model Context Protocol (MCP). Leonar ships a native MCP server, so you can connect Claude Desktop, GitHub Copilot, or any MCP-compatible client and let the AI read and write your workspace directly. Every core workflow is exposed as a named tool: `search_companies`, `create_company`, `search_candidates`, `create_contact`, `enrich_contact`, `create_deal`, `enroll_contacts_in_sequence`, `send_message_to_contact`, `create_note`, and `create_task`, among others. Combined with Claude or ChatGPT tool calling, this means your AI agent takes approved actions in your CRM without you clicking every button. MCP is not unique to Leonar, since a few other recruiting platforms now expose one too, so the connection pattern below carries over even if you use another tool that supports it. Prefer a fully custom build? The same actions are available over the REST API at `/api/v1/`. Here are three workflows that become possible: ### The targeting workflow: from a researched company list to an enriched contact This workflow starts with research from job boards, company databases, or your own market knowledge. Once you provide a target list, the AI can handle the CRM steps: **Step 1: Identify target companies outside the CRM.** Use job boards or another company-research source to build a list with each company’s name, domain, industry, and the hiring signal that makes it relevant. **Step 2: Check and deduplicate your CRM records.** The AI calls `search_companies` to search companies already stored in your Leonar workspace by name or domain, with optional industry and owner filters. It can use `create_company` for a target that is not yet stored. **Step 3: Add the decision-maker.** Once your research source has identified the VP of Talent, Head of HR, or hiring manager, the AI adds that person to your CRM with `create_contact`. **Step 4: Enrich the contact.** The AI triggers `enrich_contact` to find the person’s work email and phone number. **Step 5: Create a deal.** The AI opens a deal with `create_deal` linked to the company, with the estimated value and expected close date based on your typical sales cycle. The external company research in step 1 remains a separate input. After you supply that target list and the relevant decision-makers, steps 2 to 5 can run through approved CRM tools while you review the results. ### The messaging workflow: AI-drafted outreach sent through real channels Once contacts are in your CRM with enriched email addresses, the AI can draft and send outreach directly: **Option A: Enroll in a sequence.** If you have built multi-step outreach sequences across LinkedIn, email, and WhatsApp, the AI calls `enroll_contacts_in_sequence` to add contacts to the right campaign. The sequence handles timing, channel selection, and follow-ups automatically. The mechanics are the same as an [outbound recruiting sequence](https://www.leonar.app/blog/outbound-recruiting/), pointed at future clients instead of candidates. Because those steps can include AI variables and even a LinkedIn voice note, each enrolled prospect gets a message that references their specific hiring needs. **Option B: Send a one-off message.** For high-value prospects that deserve a personal touch, the AI drafts a message and sends it with `send_message_to_contact` on your preferred channel: email (with a custom subject line), LinkedIn message, LinkedIn InMail, or WhatsApp. You review the draft and approve it, or let it send automatically if you trust the prompt. The beauty of this approach is that every message lives in your CRM’s conversation thread. When the prospect replies, your team sees the full context. There’s no gap between what the AI sent and what your recruiter follows up on. ### The nurturing workflow: automated pipeline monitoring and re-engagement This is the workflow that pays for itself the fastest because it recovers revenue from deals your team has already invested time in: **Step 1: Scan the pipeline.** The AI calls `search_deals` and filters for open deals with no activity in the past 7 to 14 days. **Step 2: Pull context.** For each stale deal, the AI reads the conversation history with `list_conversation_messages` and reviews the notes attached to the deal so it knows exactly where the relationship left off. **Step 3: Draft a follow-up.** Based on the last exchange, the AI writes a contextual message. If the prospect asked about pricing, the follow-up includes a case study with ROI data. If they went silent after an initial positive response, the message offers a new angle (maybe a relevant industry report or a “thought you’d find this interesting” share). **Step 4: Send or queue for review.** Depending on your comfort level, the AI either sends the follow-up directly with `send_message_to_contact` or logs a `create_task` for a team member to review and send manually. Running this workflow daily means no deal ever goes cold by accident. Your AI agent becomes the most reliable follow-up machine your agency has ever had. ## Prompts and templates you can use today You don’t need an API connection to start using AI for business development. Here are prompts and templates you can copy into Claude or ChatGPT right now. ### Prompt: identify high-potential target companies ``` You are a business development strategist for a recruiting agency specializing in [YOUR NICHE]. I want to identify companies likely to need external recruiting help in the next 30-90 days. Here are 10 companies I found with open roles in my niche: [PASTE COMPANY NAMES AND OPEN ROLE COUNTS] For each company, analyze: 1. Urgency signals (number of roles, posting age, seniority mix) 2. Likelihood they use an agency (company size vs. open roles ratio) 3. Estimated deal value (based on typical placement fees in this niche) Rank them 1-10 by priority and explain your reasoning in one sentence per company. For the top 3, suggest the specific person I should contact (title and likely department). ``` ### Template: personalized agency introduction email ``` Subject: [COMPANY]'s [SPECIFIC ROLE] search: quick thought Hi [FIRST NAME], I noticed [COMPANY] posted [NUMBER] [ROLE TYPE] roles in the past [TIMEFRAME]. That's a meaningful ramp-up, especially with [SPECIFIC CONTEXT: e.g., "your Series B closing in Q4" or "the new Austin office build-out"]. We work exclusively with [NICHE] companies at your stage, and the pattern I've seen is that internal teams hit a ceiling around [NUMBER] concurrent searches. Beyond that, time-to-fill starts stretching past 45 days. I put together a short salary benchmarking report for [ROLE TYPE] roles in [LOCATION]. Happy to send it over: no strings attached. Worth a 15-minute call this week? [YOUR NAME] [AGENCY NAME] ``` This template works because it leads with a specific observation (not a pitch), offers free value (the salary report), and makes a small ask (15 minutes, not a demo). If you want more outreach templates specifically for [staffing agency introduction emails](https://www.leonar.app/blog/staffing-agencies-introduction-email-clients/), we’ve published a full library with response rate data. ### Prompt: draft a nurturing sequence for stale deals ``` I have 8 prospects in my recruiting agency's sales pipeline who haven't responded in 10+ days. For each one, I'll give you: - Their name, title, and company - The last message exchanged - Their deal stage (discovery, proposal, negotiation) Draft a 3-message nurturing sequence for each prospect: - Message 1 (send now): Re-engage with a new angle or value add - Message 2 (send in 5 days): Share a relevant case study or insight - Message 3 (send in 10 days): Honest "should I close this out?" message Rules: Keep each message under 80 words. Never say "just checking in" or "circling back." Each message must offer something new. [PASTE PROSPECT DETAILS] ``` ## Common mistakes when using AI for agency business development **Letting the AI send without review (too early).** Start by having the AI draft messages that you review before sending. Build trust in its output over two to three weeks before enabling any automatic sending. Even then, keep high-value prospects on manual review. **Providing thin context.** The quality of AI output is directly proportional to the context you provide. “Write an email to a prospect” gives you a generic email. Providing the prospect’s name, company, role count, recent news, and your specific offer gives you something worth sending. **Over-automating the relationship.** AI agents are excellent at the first 80% of business development: research, drafting, scheduling, and follow-up reminders. But closing a deal still requires human judgment, trust-building, and negotiation. Use AI to get you to the conversation faster, not to replace the conversation itself. **Ignoring your existing pipeline.** Agencies often get excited about AI-powered prospecting and neglect the deals already in their CRM. The highest-ROI use of AI is usually re-engaging stale deals, not finding new ones. According to research from the Harvard Business Review, acquiring a new customer costs five to seven times more than retaining an existing one. **Not tracking results.** Set up basic metrics from day one: messages sent, response rates, meetings booked, and deals created. Compare AI-assisted outreach against your historical benchmarks. If you’re using a CRM with [built-in recruiting automation](https://www.leonar.app/blog/recruiting-automation/) and analytics, this data is already being captured. ## Frequently asked questions ### Can AI agents replace a dedicated business development team? Not entirely. AI agents eliminate the most time-consuming parts of BD (research, writing, follow-up tracking) but don't replace relationship-building, negotiation, or strategic decisions about which markets to enter. Think of them as giving every recruiter on your team BD capabilities without hiring a separate BD person. A solo agency owner using AI agents effectively can match the outreach volume of a team of three. ### How much does it cost to set up AI-powered client acquisition? The tools themselves are affordable. Claude Pro or ChatGPT Plus costs $20/month. A recruiting CRM with connected workflow access starts at standard subscription pricing. The real investment is time: expect to spend 10 to 15 hours in the first month building prompts, testing workflows, and refining your sequences. After that, the system runs with 30 to 60 minutes of daily oversight. ### Is it ethical to use AI for outreach? Will prospects know? AI-assisted outreach is no different from using email templates, CRM sequences, or a copywriter. The message is still sent from you, reflects your expertise, and offers genuine value. What matters is the quality of the message, not whether a human or AI typed it. The ethical line is deception: don't use AI to fabricate case studies, fake testimonials, or misrepresent your agency's capabilities. ### What's the difference between using ChatGPT manually and connecting it to your CRM? Manual use means you copy data from your CRM into ChatGPT, get a response, and paste it back. It's useful but still involves significant manual work. A CRM connection means the AI reads your CRM data directly, takes actions (create contacts, send messages, update deals), and runs workflows autonomously. The difference is similar to the difference between sending emails one by one and using an outbound recruiting sequence: same principle, dramatically different scale. ### Which AI model works best for recruiting BD? Claude (by Anthropic) and ChatGPT (by OpenAI) can both handle business development tasks. For connected workflows, both support tool calling, which is what lets them read from and act in your CRM through approved actions. Test each model with the same real prompt and choose the output that best fits your agency. The quality of your prompts and the data you provide matter more than the model name. ### How do I get started if I'm not technical? Start with the manual approach. Open Claude or ChatGPT, paste in the prompts from this guide, and practice generating outreach for your real prospects. Once you see the value, explore connecting to your CRM. Modern recruiting platforms can support MCP (Model Context Protocol) which makes the connection possible through a simple settings file, no coding required. If you want the full custom integration, most agencies partner with a freelance developer for the initial setup, which typically takes a few days. Not sure which plan fits your team? Answer 3 quick questions and we will recommend the best option for your hiring workflow. How large is your recruiting team? What is your main challenge? Are you an agency or an in-house team? Your recommended plan [See pricing details](https://www.leonar.app/pricing/) staffing ai-recruiting business-development outreach ![Pierre-Alexis Ardon](https://www.leonar.app/_astro/pierre-alexis-ardon.ByBiMn-t_2wY0oT.webp) Author [Pierre-Alexis Ardon](https://www.leonar.app/authors/pierre-alexis-ardon/) Co-founder Pierre-Alexis Ardon is co-founder of Leonar, where he focuses on building AI-powered recruiting systems, sourcing automation, and search optimization. With a background in engineering and over 7 years working at the intersection of artificial intelligence and talent acquisition, he designs the algorithms that power Leonar's candidate matching and outreach automation. Pierre-Alexis advises recruitment agencies on their digital transformation and regularly publishes analyses on how AI agents are reshaping HR workflows. He is passionate about making advanced technology accessible to recruiters who are not engineers. AI recruiting systems Sourcing automation Recruiting analytics AI agents for HR [LinkedIn](https://www.linkedin.com/in/ardonpa/) ## Related articles - ![Agency recruiter marketing a most placeable candidate to hiring managers](https://www.leonar.app/_astro/most-placeable-candidate.DbF9AJ-a_1WsApy.webp) Staffing ### [Most Placeable Candidate: The MPC Marketing Playbook](https://www.leonar.app/blog/most-placeable-candidate/) - ![Staffing agency owner reviewing client lead sources and hiring intent signals on a business development dashboard](https://www.leonar.app/_astro/lead-generation-staffing-agencies.oBMqfa0N_Z1ULbb1.webp) Staffing ### [Lead Generation for Staffing Agencies: Sources That Convert](https://www.leonar.app/blog/lead-generation-staffing-agencies/) - ![Recruitment business development: the complete guide for agencies](https://www.leonar.app/_astro/recruitment-business-development.B9Au5lqK_ZJT64Q.webp) Staffing ### [Recruitment business development: the complete guide](https://www.leonar.app/blog/recruitment-business-development/)