Picking Recruitment Partners: What Makes an Expert, and Do You Need One?

I’m definitely not an expert writer and was overly ambitious with the idea of fortnightly digests, not realising how much thought and effort writing actually requires, especially with all the last-minute complexities that recruitment throws at you. So, moving forward, I’ve decided to write monthly instead.

This month’s topic is something that affects me personally—something I’ve been guilty of myself: being the self-proclaimed "immediate expert."

The Problem
For any business partnering with an agency, it’s vital to use the right people for the job in order to get real value. For example, I wouldn’t ask a tiler to build an extension for me, even though they work in construction.

However, when it comes to hiring AI talent, many businesses either use generic tech recruitment agencies or, sometimes, even a general recruitment agency they've worked with in the past for non-tech roles. They often struggle to hire top talent. When I ask why they don’t use a specialist agency in AI, I often hear a common objection: “They all say they’re experts in AI recruitment.”

It’s true. A quick search on LinkedIn reveals a vast number of AI specialist recruiters. When you add to that the flood of LinkedIn messages, emails, and calls hiring managers receive from 'AI experts,' it’s easy to see why they’ve lost faith.

Mo the Java Expert?
When I started my first recruitment job back in 2015, I was introduced to my team and told I’d be working the Java market, and was now a “Java Specialist.” I didn’t feel much like a specialist, nor did I find Java development interesting. But every pitch I made included an introduction as a Java Specialist. The caveat, explained by my manager, was that a specialist is simply someone who exclusively recruits in a particular space. If I ever got stuck on a call, an actual expert would listen in and guide me on what to say.

Anyway, I stopped recruiting Java developers after a few weeks when I found something I was more interested in (Big Data). I made it clear that while I recruited exclusively in that space, I was by no means an expert.

So, What Is an Expert?
I don’t know of any accreditations or qualifications that verify a recruiter’s ability in a certain field. So, how can you tell if someone is an expert?
I came into recruitment from the fitness industry. As a Personal Trainer, we’d earn titles like Master Trainer and Elite Trainer after delivering a certain number of sessions. This felt like a fair metric to me. I mean, pilots value flight hours in a similar fashion, right?

I looked into it, and there’s a popular guideline suggesting that 10,000 hours generally makes someone an expert in a subject. When I did the calculations (8 hours x 5 days x 47 weeks = 1,880 hours), I realised it would take 5-6 years in the field to be considered an expert.

Do We Really Need an Expert?
If you’re hiring in the AI space, I’d say you do. There are two aspects of recruiting in this space. The first is having a level of technical understanding of the nuances in AI, including knowing who is doing what and where. With the AI landscape constantly evolving, this is best achieved by being fully immersed in the sector.

While your technical team will have an excellent understanding of the technology you’re using, they might not have the recruitment experience that’s needed alongside it. Utilising the plethora of tools and techniques to identify and engage suitable candidates is also a full-time job. Dedicated internal TA teams are great at this, but unless you’re continually hiring AI talent, most businesses won’t have the need for such a team.

So, How Do We Find an Expert?
With the countless AI recruitment experts popping up, how do you figure out who’s real and who isn’t?

Well, the proof is usually in the pudding. But to avoid tasting a salty, watery dessert, you could take steps to filter the people you work with.

Having recruited AI recruiters for my teams, I’ve faced a similar problem and did some of the following:

  • LinkedIn Profiles are great resources – Go beyond the description of their current role.
  • LinkedIn Posts – Posts about AI would indicate an interest in the area. How far back does it go? I’ve seen recruiters post two times a day for a month, but before that, they were posting about UX designers for two years.
  • Jobs Advertised – Not all recruiters advertise all jobs. But if you see adverts for .NET Developers and none for Research Scientists, that’s a red flag in my books.
  • The Companies – Check their current company. Are they specialists in AI? What about their background? Look at others in the business. If 80% of the company is hiring lawyers, accountants, and surveyors, that should raise questions.
  • Recommendations – I’ve been collecting LinkedIn recommendations from the beginning as a transparent way to validate my experience. I know a highly respected competitor who has many more than me, so I’m not the only one. But not all recruiters do this. Many are conscious about other recruiters poaching their clients.
  • Mutual Connections – When a former manager sent me profiles of recruiters to interview for my team, I used to look at our mutual connections. If they’ve operated in the same space as me for a number of years, I’d expect hundreds of mutual connections. I know competitors with whom I have thousands of mutual connections. If you have a TA team, have them check how many mutual connections they have and who they are. If you have a technical team member with an active LinkedIn profile, you can also check with them.

Author Bio

author

Mo Khaleed’s been in the data science game since 2015. As Principal Consultant he specialises in working with start-ups and scale ups and is connected to some of the best of the best in UK data science. If you want someone that understands the future of data science with your best interest at heart, email him. Like, now.