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HBR IdeaCast

Where McKinsey—and Consulting—Go From Here

30 min episode · 2 min read
·
Bob Sternfels

Episode

30 min

Read time

2 min

Topics

Career Growth, Productivity, Relationships

AI-Generated Summary

Key Takeaways

  • AI workforce integration: McKinsey now employs 40,000 humans and 20,000 AI agents, up from 3,000 agents eighteen months ago, expecting one agent per human within eighteen months rather than the originally projected 2030 timeline for this transformation.
  • Outcomes-based consulting model: One-third of McKinsey's revenue now comes from underwriting client outcomes rather than traditional advisory fees, with the goal of reaching majority revenue from this model, aligning consultant incentives directly with measurable client results.
  • Talent selection overhaul: Analytics on twenty years of internal data revealed McKinsey screened for wrong criteria—resilience from setbacks, teamwork experience, and learning aptitude now matter more than perfect academic records from 500 elite pathways previously prioritized.
  • Post-AI skill priorities: AI excels at linear problem-solving but lacks aspiration-setting, judgment, and discontinuous creative thinking, prompting McKinsey to recruit liberal arts majors and focus on leadership capabilities that remain durable in an AI-augmented world.

What It Covers

McKinsey global managing partner Bob Sternfels discusses the consulting firm's centennial transformation, including deploying 20,000 AI agents, shifting from advisory to outcomes-based work, and fundamentally changing talent recruitment beyond traditional elite pathways.

Key Questions Answered

  • AI workforce integration: McKinsey now employs 40,000 humans and 20,000 AI agents, up from 3,000 agents eighteen months ago, expecting one agent per human within eighteen months rather than the originally projected 2030 timeline for this transformation.
  • Outcomes-based consulting model: One-third of McKinsey's revenue now comes from underwriting client outcomes rather than traditional advisory fees, with the goal of reaching majority revenue from this model, aligning consultant incentives directly with measurable client results.
  • Talent selection overhaul: Analytics on twenty years of internal data revealed McKinsey screened for wrong criteria—resilience from setbacks, teamwork experience, and learning aptitude now matter more than perfect academic records from 500 elite pathways previously prioritized.
  • Post-AI skill priorities: AI excels at linear problem-solving but lacks aspiration-setting, judgment, and discontinuous creative thinking, prompting McKinsey to recruit liberal arts majors and focus on leadership capabilities that remain durable in an AI-augmented world.

Notable Moment

Sternfels reveals his son strategically quoted McKinsey's own research on valuing learning aptitude over subject mastery to justify changing his college major for the third time, demonstrating how internal research findings can unexpectedly influence personal decisions.

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Episode Transcript

Deal is not just another payroll platform. It's one your team might actually enjoy. HR, IT, and payroll together finally. Built in house, built for peace of mind. Visit deel.com/hbr. The best b to b marketing gets wasted on the wrong people. When you want to reach the right professionals, use LinkedIn ads. Spend $250 on your first campaign on LinkedIn ads and get a $250 credit for the next one. Just go to linkedin.com/ideacast. That's linkedin.com/ideacast. Terms and conditions apply. I'm Adi Ignatius. I'm Alison Beard, and this is the HBR IdeaCast. Alright, Allison. This question's gonna seem random, but I promise you it's not. What was your major in college? I was a double major in journalism and politics at Washington and Lee University. Okay. I was history at Haverford, another liberal arts college. If you're like me, you probably figured that your majors equipped you well for something like journalism, but maybe not so well for something like management consulting, which has tended to recruit people who studied economics or engineering, you know, or business. Yeah. I always thought of consulting and finance as a place where sort of all the most ambitious, highest achievers, most capitalistic students wanted to go. And those firms definitely focused on the Ivy League and the big universe space. The world is changing. We know that. AI is remaking everything, including the world of management. And my guest today, McKinsey's global managing partner, has a lot to say about how it is rethinking its business in this era. So McKinsey already views its first AI agents as very much part of its workforce and is rapidly expanding that part of its team. But while AI is really good at linear problem solving, it's not so good at out of the box thinking, which means McKinsey is rethinking its talent needs. I'm not gonna spoil it, but your journalism politics double major might line up well with what the consulting giant is increasingly looking for. So here's my interview with Bob Sternfels, global managing partner at McKinsey, which is celebrating its one hundredth anniversary this year. So I wanna start. McKinsey is turning, maybe has turned 100. HBR, by the way, we're a 103. So welcome to the Century Club. You know, how would you summarize the company's one hundred year legacy? To what extent has McKinsey created the ideas that have shaped the business world, or to what extent is it about identifying and suggesting best practices that come from elsewhere? I guess I would start with the nature of how we do our work. And the idea is, look, we cocreate with our clients. And when we're at our best, it is figuring out how do we help clients get to places they can't get to themselves. The whole notion, in some ways, of credit, of did you create something novel, or did you comp you know, best practice. Maybe the way we frame is we're co creating with clients …

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