It was a watershed moment when traditional headhunting practices changed standard recruitment procedures. Headhunting replaced a reactive process that attempted to match individual candidates to as many positions as possible with one that shifted the focus to matching highly-specific skill sets to find the most appropriate candidate for a specific position with a specific company.
Today, headhunting is on the cusp of another radical revision. Increasingly, headhunting algorithms are being used to churn through the voluminous employment and candidate data that exists across the internet in an effort to find the right candidate for employers more proactively than ever before.
While humans have access to the same information as a computer, headhunting AIs can scan through this data much more rapidly, using machine learning to find patterns in the data that human headhunters might miss. This makes it possible to discover candidates that might get left out of traditional searches. However, the technology isn’t without its issues, and even with all of its promise, it can’t replace traditional headhunting practices.
How AI Headhunting Can Improve Traditional Headhunting
Traditional headhunters are frequently tasked by employers to find the very best candidate based on extremely specific criteria. This can be problematic for two reasons. The criteria that are chosen usually eliminate a large number of potential candidates before they can be considered. Because most companies are using the same rough criteria, which means they’re all competing for a small percentage of the total candidate base, causing many positions to remain unfilled.
AI headhunting flips this process upside down. Because AIs are capable of considering tens of thousands of candidates simultaneously, they can generate updated candidate lists, in real-time, when the operator changes the search criteria. This helps you discover highly-qualified candidates that were previously missed because they weren’t exact matches to your search criteria.
Of course, this assumes that the information the AI is pulling comes from a detailed, accurate database. AIs are very good at finding patterns, but the patterns it finds aren’t useful if the data they’re based on is thin, scattered, or inaccurate. With good data, they can generate unique insights to help headhunters do their jobs more efficiently.
AI headhunting algorithms are able to find and focus on more information than a human headhunter can, and are able to make connections between specific skills that could be better indicators of job performance than standard criteria. This again means that you can find excellent candidates that would have been blocked from view by traditional methods.
How AI Headhunting Could Impact Traditional Headhunting
As the technology develops you’re likely to see self-service headhunting applications hitting the market. These will allow employers to hunt for the right prospect themselves, eliminating the role of traditional headhunters. These apps will further shift headhunting practices into a proactive space that considers candidates that aren’t actively looking for a job but could be wooed away for a better position.
It’s certainly possible that one day headhunting AIs will be sufficiently sophisticated to handle the entirety of the headhunting process, but this is still a long way off. For now, AIs can help facilitate the beginning of the process, but the results they generate still need to be vetted by experienced headhunting professionals.
For the foreseeable future, AI headhunting algorithms can be useful, complementary tools alongside traditional headhunting practices, but they shouldn’t be used on their own. You need the human touch that only a traditional headhunter can supply.
Traditional Headhunting Can’t Be Replaced
AI can passively parse huge amounts of data about tens of thousands of candidates in the time it would take a human headhunter to properly vet a single candidate. This would seem to be a win no matter how you view it. However, this passive approach is limited in a number of ways.
For one, an AI headhunting algorithm is only as good as the data it has access to. Because the data collection process is automated, there isn’t a person verifying data quality, and the AI isn’t smart enough to question whether the data it’s accessing is accurate or complete.
As a result, the matches headhunting AIs make can be faulty, or worse, biased. While the AI itself has no bias, the data it gathers could be, and this biased information will be processed unquestioningly by the AI. A human headhunter can look for and eliminate mistakes in his or her thinking. AIs don’t have that sort of reflective capacity, and so if one makes a mistake the faulty recommendation will be offered without any warning.
The other difficulty in trusting an AIs output is that the more an AI learns through unguided machine learning processes, the harder it becomes for humans to understand how the AI makes its decisions. In short order, it becomes impossible for a person to comprehend how the AI works.
This is problematic because employers have no choice but to blindly trust the AIs recommendations. There’s simply no way to verify what it was that caused the AI to pick one candidate over another. It then becomes difficult to follow up with candidates and verify their qualifications.
For Now, Traditional Headhunters Are Still the Best Choice
AI headhunting is an interesting technological development, one that will likely become a larger part of the headhunting process in the future, but traditional headhunting is still immensely useful in finding and qualifying potential candidates. Human headhunters aren’t perfect, but they can rely on intuitions honed by years of experience. They can’t parse data as quickly, but they have an innate sense of what makes a good candidate match. This means they can do more with less information.
AIs are great with data, but they can’t understand human psychology. They see information, but they can’t see the person. Good headhunters rely on information about a candidate’s skills, work history, and qualifications. But they also use ephemeral human qualities that AIs can’t conceive of. These could be subtle personality traits that might render a candidate that’s otherwise a perfect paper match a terrible fit for a specific company.
Humans are simply too complex to be reduced to cold, clinical datasets. AIs are able to see patterns in the data the humans will miss, but they’ll never truly understand the person that the data represents. One day it might, but that’s years in the future. For now, traditional headhunters will continue to be your best option for finding the right candidate for our open positions. It might not happen as quickly, but you’re more likely to find an ideal candidate with staying power.