McKinsey AI Interview Being Piloted As A Part of Final Round Interviews

Key Insights:

• McKinsey's AI Interview Is Live: McKinsey has introduced an AI-driven component in its U.S. final-round interviews where candidates collaborate with Lilli, the firm's proprietary AI platform, to complete problem-solving and synthesis tasks.
• Core Prep Still Comes First: You won't reach the AI portion unless you pass the case interview and PEI first. Nail your fundamentals before adding any AI prep to your routine.
• The Bar Is Baseline Competence: McKinsey isn't testing prompt engineering mastery. It's testing whether you can ask clear questions, iterate on outputs, and apply good judgment, exactly the way a consultant would.

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Originally published December 11, 2025: In a shift that could redefine how top consulting talent is selected, McKinsey & Company has introduced an AI-driven interview as part of its U.S. final-round assessment, according to internal sources familiar with the recruiting process. This AI interview component is currently being piloted rather than fully rolled out, and the new interview style is most likely to be encountered by candidates interviewing for the Business Analyst position. We expect more candidates to begin to encounter this AI interview in Spring/Summer 2026 in conjunction with McKinsey's new, accelerated recruiting timeline.

It includes three separate interviews, with the final component requiring candidates to prompt and collaborate with Lilli - McKinsey’s proprietary AI platform - to successfully complete the evaluation. At this point, this is a non-evaluative pilot being used to help McKinsey understand future use cases.

However, the move still signals a watershed moment for consulting recruitment: At some point, if candidates cannot work effectively with AI, they may not receive an offer.

What is the McKinsey AI Interview?

The McKinsey AI interview is a component of McKinsey's U.S. final-round interview process in which candidates collaborate with Lilli, McKinsey's proprietary AI platform, to complete problem-solving, synthesis, and scenario-based tasks.

A New Era: The AI Interview Arrives

In the newly updated final round, candidates are presented with a series of tasks that must be completed through live interaction with Lilli. This includes problem-solving questions, synthesis challenges, and scenario-based prompts where Lilli serves as both a research engine and a collaborative partner.

Early testers have reported experiences of “prompt anxiety” - a term used to describe uncertainty around how to query the AI effectively. The reaction mirrors sentiments previously documented among McKinsey consultants when Lilli was deployed internally and began handling large volumes of research and synthesis tasks. As of 2025, Lilli processes more than 500,000 prompts per month, which, for a company with ~40,000 employees, signals slow adoption. Still, the tool is becoming more deeply integrated into McKinsey’s consulting workflow.

Why McKinsey Is Doing This

McKinsey has publicly stated that Lilli is central to the future of its work, enabling teams to access firm-wide knowledge in seconds, automate slide creation, streamline synthesis, and augment client deliverables. Reports from Business Insider and Entrepreneur highlight how internal AI tools are already reshaping project workflows - sometimes replacing tasks historically assigned to junior consultants.

Given that reality, McKinsey’s new interview format is a preview of the job itself (just like the McKinsey case interview that candidates have to ace just to get to this point).

Candidates who join McKinsey will be expected to collaborate with AI daily, and the firm appears determined to test whether there's alignment between who can succeed in the interview and who stands out on the job.

When This Becomes Evaluative, You Still Should Not Freak Out

This change is notable, but it shouldn’t derail your preparation plan.

1. Don’t over-emphasize AI prep. You won’t even reach the AI portion unless you first pass the case interview, PEI, and behavioral components. Your core interview fundamentals still determine whether you advance.
2. Most of McKinsey’s scoring remains case & PEI weighted. The firm’s evaluation has historically leaned heavily on structured problem-solving (case) and demonstrated leadership/impact (PEI). That foundation still drives the hiring decision.
3. The bar is likely baseline competence, not mastery. The AI interview appears designed as a final practical filter: can you collaborate with an AI tool in a reasonable, professional way? You don’t need advanced "prompt engineering" - just enough comfort to ask clear questions, iterate, and use outputs thoughtfully.
4. McKinsey tells candidates ahead of the interview what they need to know and how to prepare.

Bottom line: Keep preparing like a normal McKinsey candidate, then add a light layer of AI fluency so you can demonstrate you’re not allergic to modern tools.

How to Prep for McKinsey’s AI Interview in 30 Minutes (Without Overdoing It)

5 Minutes: Understand the Goal

This is not a test of advanced prompt engineering. The AI interview is checking one simple thing: Can you work productively with an AI tool the way a consultant would?

That means:

• Asking clear questions
• Iterating when the first output isn’t perfect
• Applying judgment rather than copying blindly

If you can do that, you’re already most of the way there.

10 Minutes: Practice “Consultant-Style” Prompts

Open any generative AI tool and practice 3-4 realistic prompts, such as:

• "Summarize the key trends in [industry] relevant to [client objective]."
• "List the top risks and mitigations for [strategy] in bullet points."
• "Create a simple 3-point structure to answer this question."

Then refine once:

• "Make this more concise."
• "Organize this into a clear storyline."
• "What assumptions are you making?"
• "Source every data point you used."

This starts to mirror how McKinsey consultants use Lilli.

5 Minutes: Practice Applying Judgment

Take one AI output and ask yourself:

• What’s useful?
• What’s missing?
• What would I change before showing this to a client?

You don’t need to say "the AI is wrong." You do need to show you can evaluate and improve its output.

5 Minutes: Practice Explaining Your Thinking

Be ready to articulate:

• Why you asked the prompt the way you did
• How you decided what to use vs. ignore
• What you’d do next if you had more time

This signals maturity and consulting judgment.

5 Minutes: Internalize the Right Mindset

Remember:

• You already passed the case and PEI
• This is a final filter, not the core evaluation
• The bar is baseline competence, not mastery

Think of Lilli as a junior teammate, not a magic answer engine. If you can communicate clearly, structure your thinking, and stay calm & adaptive, you are more than prepared. Don’t overhaul your prep plan. Just make sure AI doesn’t feel foreign when you encounter it.

For a full prep plan, read our McKinsey Lilli interview guide.

Broader Implications for the Consulting Industry

McKinsey is the first major consulting firm confirmed to incorporate AI prompting directly into final-round interviews, but we expect other firms - such as BCG with its “Deckster” tool and Bain with “Sage” - to follow. As AI becomes embedded across workflows, prompt engineering and AI collaboration may become standard consulting skills that firms intentionally test for.

Update: Bain did follow. Its AI interview, called the immersive case, gives candidates ChatGPT, Excel, and PowerPoint to build and present a recommendation. Read our Bain AI interview guide.

This shift also raises questions for candidates: traditional prep methods focused solely on casing and personal experience stories will get you to the doorstep of an offer, but without a baseline level of AI competency, it's going become more difficult to land an offer. That's why our Black Belt prep program includes coaching on every step of the interview process, including the McKinsey AI interview.

The message is clear: AI literacy is no longer optional in consulting. For future candidates, mastering casing still matters, but so does understanding how to think, work, and problem-solve with AI.

McKinsey AI Interview: Frequently Asked Questions