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McKinsey & Co.’s interview process has always been one of the most watched hiring systems in the professional world. Most recently, the firm has begun piloting a new interview format that requires candidates to use the firm’s internal AI chatbot, Lilli, during one stage of the interview process. The goal of this exercise isn’t to test whether candidates can avoid AI, but rather to see how effectively they can work with it. So, what does this AI interview exercise entail, and what does it mean for the consulting world?
McKinsey’s AI Interview
Candidates participating in the pilot were asked to use Lilli while analyzing a case study and refining their recommendations. This exercise was not pass-or-fail. Instead, interviewers analyzed how candidates interacted with the tool.
The point is, McKinsey isn’t testing prompt engineering in the abstract. Interviewers reportedly focused on whether candidates demonstrated curiosity, judgment, and skepticism; whether they could take AI-generated output, challenge it, contextualize it, and adapt it to a specific client situation.
This mirrors how consulting work itself is changing. Consultants are increasingly expected to move beyond analysis that clients can now do internally and toward higher-level problem framing, judgment calls, and implementation.
Why McKinsey Is Doing This Now
Consulting firms are undergoing a structural shift driven by AI adoption and client expectations. McKinsey, like its peers, is spending more of its time helping clients implement AI systems, redesign workflows, and deliver outcomes. The firm shrank its workforce by more than 10% between 2023 and mid-2024 and has encouraged underperforming consultants to exit. Additional job cuts, particularly in non-client-facing roles, are reportedly planned as AI-driven efficiencies increase.
At the same time, McKinsey is expanding its internal use of AI dramatically. CEO Bob Sternfels recently said the firm now has roughly 20,000 AI agents supporting about 40,000 human employees, with a goal of reaching one agent per person in the near future. Thus, testing AI collaboration during interview seems rather logical.
What This Means for Job Seekers
The classic consulting “pyramid” of firms hiring armies of junior analysts is changing. AI can already do much of the analysis that once justified large junior classes. What firms now need are people who can check AI-output and communicate insights to clients who are themselves becoming more sophisticated (largely through the use of AI).
This also helps explain another notable shift McKinsey has acknowledged: a renewed openness to candidates with liberal arts backgrounds. Sternfels has said such candidates were sometimes deprioritized in the past, but their ability to make “discontinuous leaps” in thinking may complement AI systems that excel at pattern recognition but struggle with creative judgment.
What This Means for MBA and Grad Students
For undergraduates, the message here is that technical mastery alone is no longer enough. Of course, traditional preparation still matters, but adaptability, learning agility, and intellectual judgment are becoming more critical. In other words, candidates who can demonstrate thoughtful engagement with AI tools may have an edge.
For MBAs, the implications are arguably even bigger. MBA candidates have long been evaluated as future managers, and in an AI-enabled consulting world, that distinction will become even sharper. Firms might expect MBA hires to show stronger decision-making skills and leadership instincts in the age of AI.
Will Other Firms Follow Suit?
McKinsey has a long track record of trailblazing. In the recent past, the firm led the move toward gamified problem-solving tests, forcing candidates to rethink how they prepared for interviews. This AI pilot feels like another one of these scenarios.
Industry observers expect firms like Bain and BCG (Boston Consulting Group) to follow suit. As consulting firms continue investing heavily in AI, the way they evaluate junior talent will inevitably change. A recent example of this is Accenture’s $1 billion acquisition of Faculty in which the firm seeks to enhance its AI capabilities.
The bottom line is, consulting interviews have always been a proxy for how candidates will perform on the job—if the job is changing, the interview must also change.
How Candidates Can Prepare
The takeaway here shouldn’t be that you need to memorize AI prompts or learn how to outsource your own thinking to AI. Competitive job seekers will need to demonstrate comfort working alongside AI tools without deferring to them blindly, along with the ability to critique and refine AI-generated insights.
Candidates should also demonstrate genuine intellectual curiosity and the ability to learn from failures. Indeed, the consultants of the future won’t be defined by who can generate answers faster, but by who can ask better questions, apply good judgment, and deliver insight in an increasingly AI-driven world.
Rob Porter is an editor at Vault.
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