In this solo presentation, Mohammed Adris argues that AI should be viewed as an efficiency engine, not a growth engine, for recruitment firms. He distinguishes two ways recruiters use AI: "hide" (building workflows that keep them busy without generating revenue) versus "amplify" (automating proven, revenue‑generating processes). The core insight is that proprietary data and contextual knowledge are the true competitive assets; AI merely processes that data. Adris outlines a task taxonomy separating mechanical, repeatable tasks (e.g., outreach sequencing, CRM updates, follow‑up emails) that can be handed off to AI from persuasive, judgment‑heavy tasks (e.g., relationship building, candidate trust) that must remain human‑driven. He provides a practical framework: identify the single biggest friction point, automate it thoroughly, validate the result, then move to the next task—never attempt massive, simultaneous overhauls. He illustrates how this approach can boost each recruiter’s revenue by 15‑20% without hiring, raising the overall bar for recruiter performance. Throughout, he stresses the importance of feeding AI with a decade‑plus of internal email and CRM data to create personalized, high‑impact outputs. The talk concludes with a call to action to join his "school group" for templates and tool recommendations, and a reflective question prompting recruiters to prioritize real business‑building activities over AI tinkering.
Chapters
AI is not going to grow your recruitment business. I know that's not what you want to hear right now, especially if you've been spending your evenings watching demos and building workflows and testing tools. And I know there are people all over the internet telling you the complete opposite, but I've been running my own recruitment business now with a team of 14 for over a decade, and I use AI tools every single day. And I can tell you that just with complete confidence that AI is not a growth engine for your business.. It is an efficiency engine. And understanding the difference between those two things is the most important thing that I can actually teach you right now. Because the mistake I keep watching people make, and I was starting to make the same thing myself before I caught it, is that they are treating AI like the answer to a growth problem. And it isn't. It can't be. And once you see why, you'll know exactly what it is used for and exactly what it can't be. There are two different ways to use AI in a recruitment business, and almost everyone I see is on the wrong one. But let me break it down. One option is you use AI to hide. This doesn't sound like what it is when you are actually doing it. It looks like building a workflow or testing a new tool, automating a process. It kind of feels productive. You are learning, you're building, you're improving the business. But if you trace it back honestly and you are actually doing it, spending your time on things that don't directly result in clients or candidates or placements, You're preparing to recruit indefinitely. And the second one is that you use AI to amplify. This means that you already have something working. You already know how to write a client email and get responses. You already know which LinkedIn messages open conversations. You already know or have a process for sourcing candidates. And now you're handing that work off to software so you can do more of it faster and without hiring another person to do it manually. The difference matters because path 1 keeps you busy without making you money, and path 2 makes you more money without requiring more hours. And the test is this, and it's the same one that I run on anything that I'm building with AI: if I stopped working on this right now and spent the time on calls, emails, conversations instead, would I be better or worse off? And if the honest answer is better off, the AI project isn't ready to start yet. The gap between AI enthusiasm AI results almost always comes down to this point: that people are building workflows for problems that they don't yet have instead of solving the one problem that would actually move the needle. And this brings me to the thing that nobody talks about when they talk about AI in recruitment, which is context. Context for performance. This is the whole game, and I want to explain what I mean. Take any AI tool you want— Claude, GPT, whatever— you give it a generic prompt, Write me a cold email to a hiring manager in the accounting space. And it will write you something. It'll be fine. It won't be offensive. And it will get some responses, especially if you send it to enough people. But now imagine you gave it something different. Imagine you gave it 10 years worth of your own cold email data. The ones that got responses, the ones that didn't, the seasonal patterns, the specific language that landed in your niche, the phrases your clients respond to, the ones that put them off. You feed it your CRM notes from hundreds of client conversations. You give it your candidate communication notes and how people actually responded. Now, what does that AI produce? Something completely different. Something with literally your fingerprints on it. Something that sounds like you, understands your market, and speaks the language that your clients specifically respond back to. That's the difference between generic AI output and genuinely useful AI output. And the only person who has the data to close that gap is you. Now, I've been building my own recruitment business for over a decade. I've been in recruitment for over 13 years, and we've got 11 years worth of email campaign data, open rates, response rates, what worked, in different market conditions, what stopped working when the macro changed, the variations of email campaigns during COVID And when I feed AI that data, what comes out is not generic cold email. It's something trained on what actually produces placements in a specific niche. And you might have 2 years, you might have 6 months, whatever you have, that's your data, that's your competitive edge. And it compounds the longer you build it and the more you train it because generic AI gives generic results always. Your data is the asset, and AI is just the processor. So what does useful AI actually look like in a recruitment business? Let me show you the task list I'm working through. Every recruiter has tasks they're doing manually right now that software should be doing for them. The list is longer than most people realize. Contact a client when they advertise a job. Send an email to a candidate the moment they show up to work. Follow up with a candidate that you haven't spoken to in 90 days. Catch up with a client when it's been 100 days since you last had a conversation with them. Introduce yourself warmly to every new candidate added to your CRM. These are tasks you are doing anyway, or should be doing. With AI, you hand them off to the software and the task gets done. You just didn't have to do it. And when you look at a recruitment business end to end, from picking the niche all the way through to making a placement, there's an entire roadmap. And the AI question for each step is, can this be handed off? If yes, hand it off. If no, keep it with the person. The tasks that cannot be handed off right now are the ones that require emotional persuasion. A client who is on the fence about an interview, a candidate who needs to feel understood before they trust you, a relationship that needs warmth and really fine nuanced details that software can't replicate. Those stay with the human. And the tasks that can be handed off: outreach sequencing, CRM management, draft copy based on your own templates, data organization, follow-up cadences. These are all basically mechanical. They don't require judgment and they require consistency. So when you offload the mechanical tasks, you free up your time and your recruiter's time for the persuasive tasks. And the persuasive tasks are where the money is in recruitment. And your data is the asset. AI is the processor and your time should be on the work that no processor can do. That's exactly what I do. And here's what this means, especially if you're looking to build a team, because this part gets really interesting. A recruiter who knows how to use AI correctly is not just more efficient, they're a different kind of employee altogether. I have a team of recruiters. Each of them generate north of $200K a year. And what I'm working on right now is amplifying the output by 15 or even 20% without hiring another person. Not through cutting anything. I mean, we are still hiring people 'cause we're looking to grow. But at the same time, if I can raise every $200K, $300K, even $500K recruiter by 15 or 20%, then that just raises the bar across the entire team. So by removing all the mechanical friction from their working day and giving that time back to the things that actually drive placements, that's the AI argument in its clearest form. Not AI will do your job. The argument is AI removes the tasks that are slowing down the person who is already good at their job. And the implication of this is that the bar for what makes a good recruiter has just gone up because a mediocre recruiter with AI tools is a mediocre recruiter. But a good recruiter with AI tools is now capable of doing the work that used to require 2 or 3 people. So if you're building your desk and wondering when AI is relevant, the answer is immediately for the mechanical work. Not eventually, like literally right now. But start with the one task that is currently the biggest bottleneck. Automate that one thing properly, confirm it's working, and then move to the next. Not all at once, one at a time. AI removes friction from the people who are already good at their job. It does not make a bad recruiter good because tools without context and tools without skill behind it is just noise. And by the way, if you're still in that process of experimenting with which tools you should and shouldn't use, if you just want the full list of all the tools and some of the templates that we use as well, then I've left some details below. There's a school group that I created and inside there I actually share all of my templates and tools that I use as well. And back to the video, I want to leave you with this question. And whenever I'm deciding whether to spend time on an AI project or spend it on actual work of running my business, then this is what I think it through. If you had to add a million a year, pounds, dollars, or euros to your recruitment business in the next 12 months, and you could only do one thing to make it happen, what would that one thing be? I've asked this to a dozen recruiters. Every single time, the answer is the same. More clients, more candidates, better relationships in the niche, maybe another recruiter, a retainer client, or even a contract desk. Not a single person has ever said Claude. Not a single person has said the answer is an AI workflow. And that tells you everything because AI belongs in the efficiency column of your business. It reduces the cost of delivery, it saves hours, it helps your existing recruiters do more with the time that they have. All of that is real and genuinely valuable. But if your business needs to grow, growth comes from the things it has always come from: more conversations with real clients and candidates, better positioning in your niche, a stronger reputation, more consistent follow-up, more placements, more deals, if whatever you're selling. And the recruiters that I see get most distracted by AI tools are the ones that are avoiding the harder, less comfortable work of getting on the phone, getting rejected, getting back on the phone. And AI is a very easy thing to feel productive about, and that's exactly why it becomes dangerous. The timing is completely wrong. Yes, use it, absolutely use it, but use it for what it is. It's an efficiency optimization, it's not growth. AI amplifies what's already working. It cannot create what isn't there. And if you're using it to avoid conversations that actually build your desk, you're not being efficient. You're hiding in a very convincing way. So let me leave you with something practical because I don't want you to finish this video and feel like AI is something to avoid. It's not. I use it every day. I'm building things with it right now. And you just need the right framework. Take one task. That's the rule. Pick the one task that takes the most amount of time and adds the least amount of friction and probably requires the least amount of judgment. Build that one thing properly, confirm it works, then move to the next one. Not 5 automations at once, not a full rebuild of your entire outreach stack, not a new tool every week because someone showed you something that looked impressive on LinkedIn. One task. For me right now, that's building a skills file for email campaign copy trained on 11 years of our own campaigns.. So when a recruiter generates a candidate, that they can produce a personalized email sequence in minutes rather than hours. And that's one thing, is specific. The same principle applies to you regardless of how long you've been building. If you are 6 months in, your biggest time drain is manually researching LinkedIn for candidates, build a process to automate that. If your biggest drain is writing follow-up emails, build a template library trained on the ones that have worked for you. If it's CRM data that you're struggling to stay on top of to enter, then find the integration that removes that manual step. Start where the friction is actually the highest in your business, not where the technology is most interesting. And always, always ask the test question before you start: if I spent this time on calls with conversations with clients and candidates, would my business be further ahead? And if the answer is yes, stop building and make those phone calls. AI is the best tool for efficiency that has ever existed. Use it efficiently and use it for efficiency, not to substitute for doing the work. Now, I want to save you some time as well because thankfully I've been through that exact same process of testing an array of AI tools. So if you just want to skip the whole testing phase, because that is what it is, it's literally you become a product demo tester and in theory you should be getting paid for it. If you want to see all the tools that I've tested, this is the video you want to watch and I will see you there.
