Tech hiring has become a bot war.

On one side, the ranks of unemployed workers keep growing from waves of tech layoffs. Promotion rates have slowed, creating a deficit of new jobs for recent grads. Meanwhile, job seekers are empowered with new generative AI tools to help automate the process of writing cover letters and applying to jobs.

That explains how 3,000 people ended up applying to a single open data science vacancy at a healthtech company this year. Top candidates for that role were given a difficult task to complete as part of the assessment. Few passed, but amongst those who did, the recruiter in charge of the role could tell that some used AI to solve the task because of the wording they used or because they outright admitted to using AI.

As GenAI makes it easier to automate applying to jobs, recruiters are being flooded with applications; according to Greenhouse, applications in January 2024 were up 71% from the previous year. In response, recruiters are turning to AI to parse through résumés.

In other words, people are using AI to write job applications that are then vetted by AI, turning hiring into a dystopian cycle of bots trying to trick bots. This predicament amplifies the weaknesses in the systems that AI is designed to improve. And it only seems to be getting worse.

Why the hiring model is broken

Over two-thirds of tech founders and execs believe the traditional hiring model is broken. Most report spending over four months on average to hire for just one role. Sourcing an entire team? It’s a huge undertaking. The most tiresome and time-consuming parts of the hiring process involve sifting through tons of irrelevant applications and wasting time on first interviews with candidates who just aren’t the right fit.

Finding the right talent has always felt like finding a needle in a haystack. Shouldn’t AI make hiring feel more like shooting fish in a barrel?

Here’s the problem: Most hiring technology isn’t up for the challenge. Tatiana Becker, who specializes in tech recruiting, told Insider that much of the AI software that advertises the ability to match résumés to jobs in nuanced ways can only match keywords. According to Becker, it cannot pinpoint attractive candidates from desirable schools or with positive job performances leading to promotions.

Is there a better way?

Over the past several years, I’ve been obsessed with the broken hiring process, which has pushed a new generation of workers to opt for the freedom and flexibility of betting on themselves as independent contractors.

That inspired me to start A.Team, a platform that assembles teams of highly-skilled tech workers from a vetted network of more than 11,000 engineers, data scientists, product managers, and designers. But as GenAI capabilities took a leap over the last year, we wondered if there was a way to rethink the hiring and team-building process from the ground up.

AI should do more than just match keywords on a résumé. With the right training data, AI should be able to help hiring managers understand each candidate’s depth of experience—particularly, whether they’ve successfully done the job before—and whether someone will be a good fit on their team.

It shouldn’t be this hard to find the right people to hire, or to find a job that matches your skill set, especially in the age of AI. The problem is, AI only knows what you tell it and so far, we’ve been feeding it not-very-meaningful data in the form of basic résumés and job descriptions.

What if hiring managers had an AI tool that could understand what the company was trying to build. And in seconds, it could suggest vetted candidates who have done the work before, based on a treasure trove of data from technical interviews, every project the candidate has worked on, and how they’ve performed on prior teams?

And on the candidate side, what if you had a digital assistant that could answer basic interview questions so you could spend your time interviewing with hiring managers who already know you’re a strong fit for the role?

That’s what we’re building with our new Team Formation AI platform because we believe the next generation of AI hiring tools will solve two crucial problems for industry leaders—finding vetted, specialized talent, and accelerating the hiring process. Hiring managers would get access to best-in-class talent to onboard in days, not months. And, most significantly, these tools could make the first round of interviews unnecessary.

By leveraging AI not just to filter candidates but to understand and assemble teams based on a deep analysis of skills and interpersonal dynamics, we may see an end to a bot war that’s gotten out of hand. In its place we might create something far more human.

Raphael Ouzan is CEO and co-founder of A .Team