AI Recruitment

In the last two months, over $300 million has been secured by AI-driven recruitment start-ups. While the interest in AI start-ups is evident, there are several reasons why the recruitment sector may be especially appealing.

David Bernard, founder of behavioural assessment firm AssessFirst, welcomes the investment, but believes that investors must carefully consider the modelling before committing the money.

There are two types of articles that currently dominate the pages of my finance and tech news outlets. The first type attempts to convince me to invest in or explore Cryptocurrency and NFTs. In truth, I tend to only have a passing interest in these kinds of articles.

The second type of article, though, does interest me. These stories concern the millions of dollars being poured into to AI-driven recruitment start-ups.

They are of particular interest to me, having created one such business myself. In 2012, I founded AssessFirst, a behavioural assessment firm driven by algorithms to make hiring, managing and developing talent better and – importantly – fairer. Back then, the desire to invest in firms like mine would have been a welcomed development for the industry, and it’s pleasing to see it happening now.

But there are caveats. I’ll explore exactly what those are, but the first question we must answer is: Why now? Why the current surge of investment in AI recruitment start-ups?



It started in December with Paradox. It was not the start-up itself, but the investors that drew my attention to the $200m investment that the company had managed to win. The principal investor company was Unilever, an enormous conglomerate which owns close to 500 brands, many of them household names. A company of this magnitude investing in AI recruitment represents a watershed.

Then, in January, SeekOut, an AI recruitment platform based in Washington, raised $115 million of financing, followed a few days later by the $2.7 million raised by Kula, a company still in the pilot user stage of its AI-recruitment development. The first business story delivered to my account on the first day of this month? News of an €8.25 million in funding secured by Jobilla, who, it won’t need pointing out, declare themselves an “AI-powered recruiting platform”.

In the background of this investment, great societal shifts are occurring. The great resignation is driving employees to change their careers and jobs in record numbers. It is hard to comprehend how impactful these changes are to the job market as we once knew it. A quarter of the UK workforce planned to resign between November and January. In the US, around 4.5 million workers resigned in a single month.

Then there is inflation. The cost of living crisis in the UK combined with narrowing talent pools hands power to employees and candidates. Sought-after personnel will seek increased pay to meet the rising cost of living, and employers will have little choice to but to pay it. Last year, the dislocation in the job market meant, on average, a 6% to 8% wage increase for new starters. In-demand sectors hiked salaries by 15% to 20%.

It is also apparent that something of mass psychological shift occurred during the pandemic. As reported by the Los Angeles Times, 40% of US employees would quit immediately if ordered to return full-time off to the office. Employees want to be flexible, with a better work-life balance and more fulfilling work. 


AI in the workplace  

If we combine those societal changes with a technologically transforming workplace, we see that behavioural-led recruitment combines two leading edge issues. These recruitment and employee changes have put them at the forefront of investor interest – it is, in effect, a new and buoyant market.

And so is, of course, the artificial intelligence market. Taken together, the millions of dollars ploughed into AI-driven recruitment start-ups is no surprise. The combination of the ‘problem’ affecting swathes of employees and businesses has a ‘solution’ provided by these platforms. Why wouldn’t you want to invest in what seems like certain success?

Now to those previously mentioned caveats. What do we mean by AI-led recruitment?

Fundamentally, we are talking about modelling and data input that relies on human intervention. Building a successful AI-led recruitment service requires precise and effective algorithms. This requires years of data analysis and relevant customisable input, so that each business is able to locate the personal traits that assure the candidate will thrive, add to and fortify the company’s success.

And this is not easy. The word ‘algorithm’ is not a synonym for ‘assured science’. We must only remember two examples to understand why: Amazon’s sexist algorithm that penalised women in its hiring process, and Zillow’s house-price prediction algorithm that could not, in fact, compute the complexities of the housing market. Making algorithmic blunders of this nature as a recruitment platform will likely be terminal.

It would magnify the problem that it sought to eliminate. 83% of candidates who experience a dissatisfactory candidate experience will reject a role when offered. The risk with an AI-led recruitment platform is that any discrepancy almost assures this outcome. There is no doubt that the fine margins of algorithmic optimisation and precision represents a degree of risk for investors.

Yet AI, properly implemented, can vastly improve this very same experience. Twenty years of data later, the AssessFirst predictive algorithms have become ever more robust in their ability to predict who can succeed and thrive in a job specific to the culture of an individual business. This modelling takes a vast amount of time to harvest – those that have such data, alongside the right human interventions, will revolutionise recruitment. Those that do not are a threat to recruitment professionals, candidates, and investors.