AI Has Made Hiring Worse—But It Can Still HelpSKIP TO CONTENTHarvard Business Review LogoHarvard Business Review LogoHiring and recruitment|AI Has Made Hiring Worse—But It Can Still HelpSubscribeSign InLatestMagazineTopicsPodcastsStoreReading ListsData & VisualsCase SelectionsHBR ExecutiveSearch hbr.orgSubscribeLatestPodcastsThe MagazineStoreWebinarsNewslettersAll TopicsReading ListsData & VisualsCase SelectionsHBR ExecutiveMy LibraryAccount SettingsSign InExplore HBRLatestThe MagazinePodcastsStoreWebinarsNewslettersPopular TopicsManaging YourselfLeadershipStrategyManaging TeamsGenderInnovationWork-life BalanceAll TopicsFor SubscribersReading ListsData & VisualsCase SelectionsHBR ExecutiveSubscribeMy AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesSign InHarvard Business Review LogoHiring and recruitmentAI Has Made Hiring Worse—But It Can Still Help by Tomas Chamorro-PremuzicJanuary 26, 2026Illustration by Samuel FinchPostPostShareSavePrintSummary.   Leer en españolLer em portuguêsPostPostShareSavePrintI have been researching, speaking, and writing about the impact of AI in hiring for years, long before large language models entered the mainstream. AI’s deep penetration in recruitment was always likely. People spend much of their lives online, including while working (or pretending to), while firms have invested trillions in digital systems designed to capture, store, and analyze the resulting data from this. A technology like AI, capable of translating this ocean of data into insight was therefore inevitable.Tomas Chamorro-Premuzic is the chief science officer at Russell Reynolds Associates, a professor of business psychology at University College London and at Columbia University, a cofounder of deepersignals.com, and an associate at Harvard’s Entrepreneurial Finance Lab. He is the author of Why Do So Many Incompetent Men Become Leaders? (and How to Fix It) (Harvard Business Review Press, 2019), upon which his TEDx talk was based, and  I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique, (Harvard Business Review Press, 2023). His latest book is Don’t Be Yourself: Why Authenticity Is Overrated (and What to Do Instead) (Harvard Business Review Press, 2025).@drtcpPostPostShareSavePrintRead more on Hiring and recruitment or related topics Talent management, Career transitions, Job search, AI and machine learning and Generative AIPartner CenterStart my subscription!Explore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceExplore HBRThe LatestAll TopicsMagazine ArchiveReading ListsCase SelectionsHBR ExecutivePodcastsWebinarsData & VisualsMy LibraryNewslettersHBR PressHBR StoreArticle ReprintsBooksCasesCollectionsMagazine IssuesHBR Guide SeriesHBR 20-Minute ManagersHBR Emotional Intelligence SeriesHBR Must ReadsToolsAbout HBRContact UsAdvertise with UsInformation for Booksellers/RetailersMastheadGlobal EditionsMedia InquiriesGuidelines for AuthorsHBR Analytic ServicesCopyright PermissionsAccessibilityDigital AccessibilityManage My AccountMy LibraryTopic FeedsOrdersAccount SettingsEmail PreferencesHelp CenterContact Customer ServiceFollow HBRFacebookX Corp.LinkedInInstagramYour NewsreaderHarvard Business Review LogoAbout UsCareersPrivacy PolicyCookie PolicyCopyright InformationTrademark PolicyTerms of UseHarvard Business Publishing:Higher EducationCorporate LearningHarvard Business ReviewHarvard Business SchoolCopyright ©2026 Harvard Business School Publishing. All rights reserved. Harvard Business Publishing is an affiliate of Harvard Business School.

AI’s increasing prominence in the hiring process has demonstrably exacerbated existing challenges within recruitment, moving beyond simple automation to introduce new complexities and, arguably, diminished the quality of hiring decisions. Tomas Chamorro-Premuzic, in his analysis, asserts that this penetration of AI into recruitment was a foreseeable outcome, given the extensive investment in digital systems focused on data capture and analysis, a landscape facilitated by the prevalence of online activity among workers and the sheer volume of data generated. Chamorro-Premuzic, through his extensive research and writings including “Why Do So Many Incompetent Men Become Leaders?” and “I, Human,” has consistently argued against relying solely on quantifiable metrics and surface-level assessments in talent selection, recognizing the inherent limitations of data-driven approaches when applied without a deeper understanding of human psychology.

The core of Chamorro-Premuzic’s argument is that AI, in its current state, is predominantly focused on identifying “signals” – easily measurable indicators – rather than truly understanding the underlying “signals” that—when properly interpreted—represent genuine potential. He contends that these systems frequently rely on readily apparent traits and behaviors, often overlooking crucial, nuanced aspects of an individual’s character, cognitive abilities, and emotional intelligence. The problem isn’t just the technology itself, but how it is being utilized and the assumptions being made about what constitutes desirable employee qualities. Furthermore, the reliance on AI tools tends to homogenize talent pools, favoring candidates that fit pre-programmed profiles, thereby restricting diversity of thought and experience.

The author highlights a crucial flaw in the current application of AI: the tendency to treat human beings as data points. Despite the considerable resources dedicated to capturing and analyzing data, AI systems lack the capacity for genuine empathy, contextual understanding, and the ability to discern subtle indicators of resilience, adaptability, and leadership potential - qualities that are often more important than technical skills. The overemphasis on readily quantifiable data can lead to a misguided focus on “safe” candidates, ignoring individuals who possess unusual or unconventional strengths.

Chamorro-Premuzic’s arguments stem from a broader perspective on human nature—namely, the recognition that competence is not solely determined by easily measurable traits. He advocates for a more holistic approach to assessment, one that incorporates psychological insights and behavioral science to identify individuals who can thrive in complex, dynamic environments. He further emphasizes the importance of subjective judgment by experienced recruiters and hiring managers, combined with a thorough understanding of the role's demands and the organizational culture. The author's concern is that the uncritical adoption of AI in hiring risks reinforcing existing biases and limiting the opportunities available to individuals who may not fit the algorithmic mold, effectively creating a diminished talent pool and hindering organizational innovation.