McKinsey & Company, one of the world’s most prestigious consulting firms, is leveraging artificial intelligence to transform its hiring practices and address unconscious bias in its recruitment process. CEO Bob Sternfels revealed on Harvard Business Review’s IdeaCast podcast that the firm deployed AI to analyze 20 years of hiring data to identify where it may have overlooked talented candidates for its coveted partner positions.
The AI analysis yielded a surprising discovery: applicants who had experienced setbacks and demonstrated resilience were significantly more likely to become successful partners at the firm. This insight prompted McKinsey to fundamentally shift its interview criteria. “It turned out we had some bias in our system,” Sternfels admitted, explaining that the firm had been overly focused on candidates with “perfect marks” rather than evaluating how they bounced back from difficulties.
This AI-driven revelation comes at a time when McKinsey is becoming more selective with its hiring. In December, the firm promoted approximately 200 employees to partner—one of the smallest classes in recent years, according to The Wall Street Journal. This represents a significant decrease from 2022, when about 400 people were elevated to partner status. McKinsey partners typically earn under $500,000 in base pay, but total compensation can reach well into the millions through bonuses and profit sharing.
The firm faces no shortage of applicants, receiving about 1 million résumés annually. In 2024, McKinsey told Business Insider it planned to hire approximately 1% of applicants, consistent with 2023 figures. The company seeks “distinctive students just starting their careers” and experts across industries ranging from technology to finance to law.
To evaluate candidates, McKinsey employs strong problem-solving assessments, including a game-based evaluation called Solve. The firm provides preparation resources to all candidates to ensure fairness, stating this approach helps “ensure candidates from any background—regardless of whether they have exposure to resources like consulting clubs—can demonstrate their distinctiveness in our process.” This AI-powered hiring transformation represents a significant shift in how elite firms identify and recruit top talent.
Key Quotes
It turned out we had some bias in our system
McKinsey CEO Bob Sternfels made this admission on Harvard Business Review’s IdeaCast podcast, acknowledging that the firm’s AI analysis revealed unconscious bias in their hiring process that had persisted for years.
This helps to ensure candidates from any background — regardless of whether they have exposure to resources like consulting clubs — can demonstrate their distinctiveness in our process
A McKinsey spokesperson explained to Business Insider how the firm provides preparation resources to all candidates, emphasizing their commitment to creating equitable opportunities in their highly competitive recruitment process.
Our Take
McKinsey’s AI-driven hiring transformation is particularly noteworthy because it demonstrates AI’s potential to challenge elite institutions’ traditional assumptions. For decades, top consulting firms have prized academic perfection and pedigree, yet AI revealed that resilience—often developed through adversity—is a better predictor of partnership success. This finding has profound implications: it suggests that traditional hiring criteria at prestigious firms may systematically exclude talented individuals who faced obstacles, potentially missing diverse perspectives and problem-solving approaches. The irony is striking—a firm that advises Fortune 500 companies on transformation needed AI to reveal its own blind spots. As AI becomes more prevalent in HR, this case illustrates both the technology’s promise for creating more equitable systems and the critical need for human oversight to ensure AI tools themselves don’t introduce new biases while correcting old ones.
Why This Matters
This story represents a significant milestone in AI’s impact on corporate hiring practices and demonstrates how artificial intelligence can identify and correct human bias in recruitment. McKinsey’s use of AI to analyze two decades of hiring data showcases the technology’s potential to uncover patterns invisible to human observers and challenge long-held assumptions about what makes a successful candidate.
The implications extend far beyond one consulting firm. As organizations worldwide grapple with diversity, equity, and inclusion challenges, AI-powered hiring analytics could become a critical tool for identifying systemic biases and creating more equitable recruitment processes. McKinsey’s discovery that resilience matters more than perfection could influence hiring practices across industries.
However, this also raises important questions about AI governance in HR. While AI revealed bias in this case, poorly designed AI systems can perpetuate or amplify existing biases. McKinsey’s experience demonstrates both the promise and responsibility that comes with deploying AI in high-stakes decisions affecting people’s careers and livelihoods. As elite firms increasingly adopt AI for talent management, this case study will likely shape industry standards for ethical AI implementation in human resources.
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Source: https://www.businessinsider.com/mckinsey-job-candidate-criteria-hiring-ai-2026-1