McKinsey & Company has taken a bold step to democratize access to interview preparation for aspiring consultants. In April 2025, the global management consulting firm launched a free AI-driven practice tool that gives candidates unlimited attempts at the quantitative case study they will face during the actual hiring process. The move is a direct response to the exorbitant fees charged by private interview coaches, which can range from $200 to $500 per hour—a barrier that often favors wealthier applicants.
Available globally to applicants for entry-level business analyst and associate roles, the tool simulates the same mathematical scenarios used in real McKinsey interviews. Marie Christine Padberg, McKinsey’s global talent attraction co-leader, explained to Business Insider that the tool also addresses a common source of anxiety: performing calculations under observation. “Doing quantitative things is one thing, but doing it while somebody’s watching you is something else,” she said.
The practice platform is not just a one-off experiment. It is part of a broader integration of artificial intelligence across McKinsey’s hiring pipeline—and a reflection of how the firm itself has changed. Since January 2025, McKinsey has been piloting the use of its internal AI assistant, Lilli, during final-round interviews for business school graduates. In this pilot, candidates are asked to use Lilli to analyze a case study, refine their conclusions, and then defend their reasoning. Interviewers evaluate not the quality of the AI’s output, but rather how the applicant prompts the system, assesses the results, and applies them to a specific client scenario. The test measures curiosity, critical thinking, and judgment—not prompt engineering skills.
The implication is clear: McKinsey is not testing whether candidates can avoid using AI. It is testing whether they can collaborate with it effectively. This distinction mirrors the transformation happening inside the firm itself. Consultants today are expected to move beyond analysis that clients can easily replicate internally. Instead, the value lies in problem framing, strategic judgment, and implementation—areas where human insight remains essential even as AI takes over routine quantitative work.
The scale of AI inside McKinsey
McKinsey’s embrace of AI is not theoretical. At the Consumer Electronics Show (CES) in January 2025, CEO Bob Sternfels disclosed that the firm now employs approximately 25,000 AI agents to support its 60,000 human employees. Just 18 months earlier, that number was only 3,000. More than 75% of McKinsey’s workforce uses Lilli on a monthly basis. The rapid scaling of internal AI tools has fundamentally altered how the firm operates—and who it hires.
The shift has already led to workforce reductions. McKinsey has cut roughly 200 technology roles as AI automates non-client-facing operations. Between 2023 and 2025, the firm’s overall workforce shrank by more than 10%. Entry-level positions have been hit hardest—precisely the roles that the new free practice tool is designed to help candidates secure. This creates an intriguing tension: the same technology that is eliminating some jobs is also being used to select for the people who will fill the remaining—and newly created—roles.
The broader labor market reflects a similar dynamic. According to job posting data, forward deployed engineer roles have surged 19 times year over year. Roles like “Claude Evangelist” command salaries of $240,000, while Chief AI Officers earn nearly $500,000. The jobs AI creates tend to pay more and require different skill sets than the ones it replaces. McKinsey’s hiring approach codifies that shift into the interview itself. The firm is not asking candidates whether they are willing to use AI. It is making AI fluency a condition of entry.
Industry-wide implications
Other top consulting firms are expected to follow McKinsey’s lead. CaseBasix, a firm that prepares candidates for consulting interviews, has noted that BCG and Bain are likely to introduce similar AI-based interview components. The ripple effects extend beyond consulting. Detroit’s major automakers have been cutting white-collar staff while simultaneously posting AI roles. Salesforce eliminated 4,000 support positions after deploying AI agents. McKinsey is simultaneously reducing its workforce and redesigning its hiring process to select for people who can work alongside the technology that is making other roles redundant.
Despite this AI-centric focus, McKinsey insists that traditional analytical skills remain essential. Padberg emphasized that “even in an AI-enabled workplace, consultants still need to understand how numbers connect and what they mean.” AI can generate reams of analysis, but it cannot yet determine whether that analysis is relevant to a specific client’s unique problem. Closing that judgment gap is exactly what McKinsey’s new interview format is designed to test.
The free practice tool makes preparation accessible to everyone, regardless of financial background. The Lilli interview component sets a new standard: if candidates cannot collaborate with AI effectively under pressure, they will not be hired. For the graduating classes of 2025 and 2026, this is a wake-up call. AI fluency is no longer a nice-to-have on a resume; at McKinsey, it is now a core part of the entrance exam.
The combination of a free, unlimited practice tool and a novel AI-based interview component represents a fundamental rethinking of how consulting talent is identified and evaluated. By lowering the barrier to preparation while raising the bar for AI collaboration, McKinsey is simultaneously leveling the playing field and redefining the skills that matter most in a modern professional environment. As the firm continues to evolve, its hiring process offers a glimpse of what the future of work might look like—one where humans and AI work side by side, and where the ability to manage that partnership determines career success.