<p>AI technologies are revolutionizing hiring—traditionally a lengthy and painstaking process—by automating and streamlining recruitment workflows. Organizations are increasingly adopting AI solutions for their potential to enhance efficiency, objectivity, and accuracy in candidate selection. While existing research has largely centered on concerns about transparency and ethics, less attention has been paid to a more fundamental question: <i>do algorithms help companies identify candidates who truly align with the unique work environment?</i> Adopting a person–environment fit perspective, this article highlights two key barriers that hinder effective talent matching in AI-driven hiring: (1) an overemphasis on job-specific qualifications at the expense of cultural alignment, and (2) the marginalization of candidates through impersonal, automated processes. If left unaddressed, these issues can contribute to higher turnover, weakened organizational culture, and diminished employer branding. To mitigate these risks, the paper outlines three strategic-level recommendations: developing customized AI models that reflect organizational culture, training general AI models with large-scale organizational data, and enhancing the candidate experience through technology and human empathy.</p>