In a recent LinkedIn post, Meghan M. Biro discusses the rapid evolution of artificial intelligence in the hiring process, highlighting concerns about its current application in talent acquisition. Biro focuses on the potential negative impacts of AI on candidate pool quality, rather than the broader debate about job displacement for recruiters.
Biro points to a critical flaw in many current AI implementations within recruitment, suggesting a self-perpetuating cycle that may not serve the best interests of organizations seeking top talent.
“It’s not about whether AI will replace recruiters, it’s about the way most organizations are deploying AI in sourcing right now is making candidate pools worse, not better.”
The AI Recruitment Cycle Under Scrutiny
Meghan M. Biro elaborates on the cycle that many organizations are inadvertently creating with AI in hiring. This cycle, as described by Biro, involves AI tools performing multiple stages of the recruitment process, potentially leading to biased outcomes.
According to Biro, the process often looks like this:
- AI writes the job description.
- AI screens the resumes.
- AI writes the resumes it’s screening.
This repetitive loop, as Meghan M. Biro argues, results in a situation where the system prioritizes candidates who best match the AI’s own generated output, rather than identifying the individuals who are genuinely the most qualified for the role’s requirements.
Assessing Human Oversight in AI-Driven Hiring
In her post, Meghan M. Biro offers practical advice for Talent Acquisition (TA) leaders grappling with these challenges. She emphasizes the importance of identifying where human judgment remains crucial in the hiring pipeline.
“The practical version of this for any TA leader: look at where in your pipeline a human is still making the actual call, and whether the quality of hires from that part of the process reflects it. It usually does.”
Biro suggests that by examining the effectiveness of human decision-making points within the AI-assisted process, leaders can better gauge the true impact of their technology choices. The implication is that human oversight often correlates with a higher quality of hires, challenging the notion that full automation is always the superior approach.
Broader Implications for Talent Acquisition
Meghan M. Biro’s analysis underscores a growing concern in the HR and recruitment technology space: the need for a balanced approach to AI integration. While AI offers significant potential for efficiency, its current deployment may be introducing unintended consequences.
As Meghan M. Biro notes, the focus should shift from merely adopting AI to strategically deploying it in ways that enhance, rather than degrade, the quality of the talent acquisition process. This involves critically evaluating how AI tools interact with human recruiters and decision-makers.
“[AI] basically one repetitive cycle where you’re selecting for whoever best matches the AI’s own output, not the best person for the role.”
Ultimately, Biro’s insights serve as a call to action for HR leaders to be more discerning about how AI is used, ensuring that technology serves the goal of finding the best talent, not just optimizing for algorithmic conformity. The conversation, as Meghan M. Biro points out, needs to move beyond the ‘if’ of AI in hiring to the ‘how’ and ‘why’ of its implementation.
📝 About This Content
This article is based on insights shared by Meghan M. Biro on LinkedIn.
📅 Originally posted on July 17, 2026 | View original post on LinkedIn →