What Does AI Mean for Recruitment?

Since the advent of Applicant Tracking Systems (ATS), those working in recruitment aren’t averse to using technology to make recruitment more cost-effective and successful. However, the use of artificial intelligence (AI) in recruitment is a whole other ball game. Does AI in recruitment mean we can do away with the specialists, still confident we’ll find the best talent?

AI in Recruitment – The Case Study

Perhaps one of the biggest names in AI in recruitment is Ideal. One of their case studies points to how their ‘talent intelligence’ enabled Canada’s largest bookshop chain, Indigo, to reduce recruitment costs by 71%. Given the vast costs of recruiting, this is a tempting road to travel. If we all start using AI in recruitment will we drastically reduce our recruitment costs?

This is where we first discover a problem. Ideal itself describes their technology as being suitable for ‘high volume hiring’. AI would definitely appear to have its place helping you sift through the vast swathes of applicants you get for run-of-the-mill jobs.

Jobs where there is a clear job specification which a machine can use to process data far faster than a human ever could are best. Also, where you’re not searching for a needle in a haystack, but are likely to find a clutch of candidates all equally capable of fulfilling the role.

Understanding the Role of AI in Recruitment

AI in every field is very much an emerging technology. We’re sure there will be changes still to come on the horizon. However, for the moment, AI in recruitment has one clear purpose: helping you make short work of the time-consuming bulk elements of recruitment. The clearest example of this is by screening applications or CVs.

Anyone who has recruited for regular positions knows the mountains of applications well. A staggering average of 24 candidates will apply for a low-level position in the UK. That’s a lot of CVs to read and screen. Many positions will command even greater numbers. AI has a place here.

However, executive-level roles don’t typically attract the same vast number of applications. Here you are very much hunting for the needle in the haystack. Even if the candidate presents themselves to you as an active candidate (which isn’t likely), the last thing you want is a computer spewing them out because they didn’t tick the right box. These candidates need the human-factor which AI can’t deliver.

Inputs and Outputs

The safest way to view AI in recruitment is regarding input and output. If you have very clearly defined quantifiable factors then AI will be valuable. For example, it is essential that a candidate has a certain level and type of qualification. If things are more ‘woolly’, for example, you need someone with ‘demonstrated leadership qualities’, then AI is going to let you down.

In some cases, this means you can use a combined strategy of AI and typical manual recruitment methods to get the best result.

AI in Recruitment’s Limitations

There’s no doubt that recruitment is an area rife with challenges if you are trying to apply AI.

Firstly, things won’t be excellent to start with. AI, for the optimal output, needs vast amounts of data. The whole concept of AI – machine learning – only works when there have been reams of ‘test cases’. To reflect human intelligence in lightning time, it needs a great deal of input to start with. If you’re an enormous organisation with dozens of same roles, that’s great. Most businesses don’t fit this model.

Then there is the issue that it’s not fail-proof. In the ‘learning’ process there will be a great deal of human input. This means there’s also the introduction of human bias into the very system you want to do things differently. AI is all about using patterns in previous behaviour to predict the future. If you have a history of recruiting a preferred age or gender, for example, this will be learned by the machine. This is dangerous territory.

When AI in Recruitment Has No Place

The issues with AI in recruitment, at the lower job levels, are surmountable. As we say, in this kind of recruitment, AI can be a valuable tool to help cut laborious recruitment processes freeing up time for more strategic decision making.

However, AI at executive levels is wandering into trickier territory. Firstly, it’s back to the needle-in-a-haystack analogy. You’re searching for the needle, and the haystack is miles away, it’s not coming to you. If you put up an AI barrier then you simply aren’t going to attract the calibre of talent you want. These candidates know their worth, so much so, that they are unlikely to submit a CV without prompting, let alone jump through AI hoops.

Next, the skill set and attributes that you need in executive level positions aren’t suitable for AI input and output. These skills and attributes are considerably less tangible. For example, it isn’t possible for a machine to seek out an individual demonstrating a skill for a competitor when it’s not even committed to paper. Only a skilled headhunter is capable of hunting down that kind of ‘needle’, or even finding the ‘haystack’.

Trust the Human Factor

The more senior the role, the more expensive it is to fill. Furthermore, the more expensive mistakes can be. They even cost businesses in terms of lost opportunity.

A headhunter is tasked with working solely with the purpose of finding the unique individual who will not just fill a position but will drive the organisation’s success. Identifying this talent is one thing, they then need to convince that talent to join you. There’s no getting around the fact that this is, without a doubt, a role impossible for machines.

Eagle Talent

AI in recruitment has its place. It should be used to support refined recruitment strategies in large organisations with overwhelming numbers of applications at lower levels. However, at the executive levels, you need the human factor.

To see how we are Eagle-eyed for your talent call us on 0203 582 2663.