Hiring the Best Talent: Myth or Reality?

In the pre-AI era, hiring the best talent often involved careful consideration and a genuine search for the best candidate. Recruiters sifted through resumes, conducted intake calls and pre hiring manager interviews, and—importantly—relied on their human judgment to select individuals whose unique combination of skills, experience, and cultural fit made them the best match. In many ways, this manual process, while inarguably less scalable, was more aligned with hiring the "best" talent.

However, the landscape has dramatically shifted in recent years. Today, the ease of job application—fueled by technologies such as “Apply with LinkedIn” and other one-click tools—has lowered the barriers to entry for job seekers. This ease is, in some ways, both a blessing and a curse. A decade ago, applying for a job required some level of intentionality; and oddly enough, the difficulty of the hiring process acted as a natural filter of potentially unqualified or mismatched applicants. Now, with reduced friction, hundreds of applicants and sometimes even thousands—many of whom are not genuinely qualified—flood systems.

One of the unintended consequences of this application surge is that companies increasingly rely on AI-driven screening tools to manage the sheer volume. The intent is noble: to use technology to identify the most promising candidates. But here lies a fundamental flaw in the system—what these technologies claim to do and what they are actually capable of doing often diverge. Despite vendor promises of “revolutionary AI,” application processes still rely on rudimentary context and keyword matching, which can easily overlook top talent that doesn’t fit neatly within the predefined AI parameters.

Internet Job Seeker Mystery Shopping

To test this hypothesis, I recently conducted an experiment. I online applied to 30 senior product manager roles in the technology sector, including 10 positions in HR Tech—an area where I have over 20 years of experience. On paper, I matched all the key criteria: skills, geography, background. Furthermore, I am the EVP of Product at a leading HR Tech company, an award-winning expert in my field whose platform was just named a 2024 Top HR Technology Product award winner, and I am also a member of the Forbes Technology Council. Yet, despite my obvious qualifications for the roles, I was rejected within a day by every single AI-powered system I applied to. Not a single person or even automated bot reached out to me with additional questions or a brief conversation.

And I suspect my experiment is not an isolated case. It’s indicative of a larger issue in today’s hiring ecosystem: are companies truly seeking the best talent, or are they satisfied with only hiring the best candidate from the pool of applicants who happen to make it past their AI filters? These are two very different things. The idea that AI technology alone, with all its current limitations, is equipped to identify the best talent is flawed. While AI can process large volumes of applicant data and make matches on defined rules, it lacks the nuance and context that, today, only a human recruiter can provide.

Consider the implications of this: companies may believe they are optimizing their recruitment processes, but in reality, they are missing out on potentially A-level candidates simply because they don’t check all the right algorithmic boxes.

One senior HR leader succinctly summarized the problem: “We’re not necessarily hiring the best—we’re hiring the best of who applied.”

In the age of AI, it’s becoming increasingly clear that companies are now hiring the best of who survives the AI screening process.

The Paradox of Hiring Top Talent

This phenomenon creates a paradox in the pursuit of top talent. If the AI filtering mechanisms in place are rejecting top candidates due to overly rigid or simplistic matching algorithms, then the entire premise of "hiring the best talent" becomes an illusion. The aspirational marketing of HR Tech vendors would have you believe that their tools can seamlessly identify the perfect candidate, but my personal experience—and the broader data—suggests otherwise.

A significant part of the problem lies in the gap between AI’s potential and its current implementation. While AI holds great promise, companies need to audit their AI matching algorithms to ensure they are not inadvertently filtering out top talent. If the AI process is filtering candidates who are only 60-80% matches, companies are settling for B-grade talent without ever knowing A-grade candidates were in the pool.

How to Mitigate Programmatic Bias

This begs the question: what can companies do to ensure they’re truly hiring the best talent? The answer, ironically, is both technological and human. AI should absolutely play a role in talent acquisition, but it must be supplemented by human oversight. Organizations that are serious about hiring the best talent should consider integrating Recruitment Process Outsourcing (RPO) firms into their strategy. RPOs can provide the necessary human oversight and ensure that AI tools are functioning as intended—sifting through not only those who meet keyword matches but also those who possess the less tangible qualities that make someone truly exceptional.

Imagine this scenario: a company is searching for a VP of Product in HR Tech. In this hypothetical, they miss the opportunity to talk to an award-winning HR Tech expert with 20 years of experience, a product-centric technology entrepreneur, and a recognized thought leader because their AI tool filtered that person out based on a rigid algorithm. This isn’t just a hypothetical—it’s the reality for countless companies today, and CEOs who want to hire the best talent should investigate their company's hiring practices. The rhetoric around "hiring the best" is misleading if organizations aren’t willing to invest in processes that go beyond basic AI filtering.

In conclusion, while the potential for AI in recruitment is enormous, the current reality shows that hiring the best talent has become a myth. Without human intervention, companies risk settling for mediocrity—hiring not the best talent, but the remnants of those who survived the algorithmic gauntlet (a teaser for next week's article).

Yours in the mystery shopping game to find out what's really happening,

Michael Beygelman | EVP, Product | WilsonHCG