00:00I think there's a potential that this is a golden age for us, a truly golden age.
00:04And the reason is the world has some really existential challenges and opportunities facing.
00:11And you've had many people come on and talk about this.
00:14But you think about this AI moment, you think about complicated geopolitics,
00:20you think about a whole reset in the energy-climate nexus, you think about changing demographics.
00:27These are all world-class problems to solve.
00:30And what we try and do is we try and work with CEOs on their most complicated problems.
00:35And at least we see over the next five years the complexity of those problems going up, not going down.
00:42So what's the biggest disruptor to any business, AI or geopolitics?
00:46Do you have to choose whether you're an ally of the U.S. or China?
00:50AI or geopolitics? It's like trying to pick, well, which kid do you like better?
00:54These are too massive.
00:57You know, I would honestly, I think they're the twin biggest issues facing us today.
01:04But by the way, I would say challenges but equally opportunities.
01:08And this is one of the things that, you know, I always talk to a, if ever I meet a
01:13CEO, I say,
01:14okay, draw a line down the center of the page and let's write challenges and opportunities from each of these
01:19topics.
01:19And it's easy to talk about the challenges.
01:23Will AI disrupt jobs?
01:24Will it dominate the energy stack?
01:27Is it going to take everybody's water?
01:28But equally, you know, could it create and unleash a wave of growth that solves many of the other crises
01:37that we face?
01:37So how do you use AI within the firm?
01:43You know, it's like you talk to every leader.
01:46This is changing so fast.
01:49And, you know, what I would say is we're doing two things.
01:55One, the first is we're trying to help our clients.
01:58This is about half the work that we're doing today with clients around the world.
02:02And large enterprises struggling with how do I really reinvent myself with AI?
02:09My costs are going up.
02:10You've talked about, you know, token costs going through the roof.
02:13We've seen many companies blow their budgets in the first three or four months of a year.
02:19And mass experimentation doesn't necessarily yield enterprise impact.
02:24So we're focusing in on how do you really get value from AI with clients?
02:28That's a client.
02:29And so how do you get value?
02:30You know, it's also difficult to integrate, right?
02:33It can't be sitting outside if you're looking at AI and tech.
02:36You're so right.
02:36It's hard.
02:38And there are, I think, a couple principles that are emerging.
02:43You know, the first is you've got to focus.
02:46If you just let a thousand flowers bloom, you will have waste in an enterprise.
02:50And, you know, our work tends to indicate that four to six end-to-end processes in any organization,
02:57and those vary based on the industry, can drive 80% of the value from AI.
03:01So first is, are you focused?
03:02And I often ask, do you know how to double your market cap through AI?
03:05If you can't do the math, good old-fashioned strategy, you're going to be inefficient.
03:11Part one.
03:12Part two is you have to change the organization model.
03:16And so my other simple answer to or question to a CEO is, do you know what your org chart
03:20looks like in three years' time?
03:22So if you can't link the value to the org change, you're not going to get the value, right?
03:28And then the last part is, how do you bring everybody along?
03:31Change is hard.
03:32And if you have a large workforce, you need to create the incentives for people to want to drive adoption.
03:38You can't force folks.
03:40And so those are some of the principles that are, I think, emerging right now.
03:44And so, Bob, what does that mean for McKinsey?
03:46Yeah.
03:47Because you've also announced the job cuts, quite significant ones.
03:50Well, you know, it's interesting.
03:52People love to latch on to half the headlines.
03:56So...
03:56Not us.
03:57Sure.
03:57No, of course not.
03:58But we're hiring in record numbers, our client-facing consultants.
04:01Record.
04:02McKinsey has two workforces.
04:03And the workforce that most of our clients understand are the people who live and breathe
04:07with the client.
04:08And we're growing that workforce quite aggressively.
04:11And we're arming that workforce with agents.
04:14So on average right now, every client-deployed consultant has about three agents.
04:19And the joke amongst...
04:20I was just with some new business analysts.
04:22The joke was, if your agents don't work all night, you will.
04:27I like that tagline.
04:28Which I loved, right?
04:28I loved it, right?
04:29Because it was a little bit of like, hey, right?
04:31You know, you got to step up.
04:33But give me a sense of...
04:34So how much of the workforce are you reducing that you can replace by agents?
04:39And how many consultants are you hiring?
04:40Is it like net?
04:41In total, I think you will see our workforce now start to rise.
04:47So we've done...
04:48Look, like all of our clients, we've really looked for efficiencies in our indirect processes.
04:53And there is value in that, in AI.
04:56And we're trying to liberate the folks who come out of that to then be redeployed to do new things.
05:03And also natural attrition.
05:05But we've kind of done a lot of that restructuring.
05:07And now we're actually focused on how do we grow the consulting base.
05:11And I think it's an exciting time because, you know, also there are a lot of folks who aren't really
05:17hiring a lot of young folks.
05:19And so we're like, hey, come.
05:21Right?
05:21This is a great place to be for a couple of years.
05:24And you think face-to-face consultants are AI-proof?
05:28Yeah.
05:29Because this is what we're all trying to figure out, right?
05:30Well, and this is, you know, this is for all of us.
05:34You know, I look at what can the models do and what can the models not do.
05:38And, you know, one of the things that starts to really rise is I think what's uniquely human in this.
05:45And so what we're starting to focus on is, okay, you're freeing up a bunch of time.
05:50You'll use that time to spend more of it with the client.
05:52What do you do with that time?
05:54And what we're finding are a couple things.
05:57The models don't set a goal.
06:00They don't set an aspiration.
06:01It's a uniquely human thing to say, hey, should we go to the moon?
06:05Should we go to Mars?
06:06And do we both believe in that?
06:08And so there's a uniquely human thing of how do we aspire?
06:12We're focused on building that skill.
06:14The other is judgment.
06:16The models don't know right and wrong.
06:18You have to train them.
06:19And so how do you work with a client to say, look, you should be the custodian of judgment in
06:25your own company.
06:26By the way, you can reference your own values to have the models reinforce the values of the company.
06:31That's a human thing.
06:32The humans have to impart what are the values of this institution.
06:35And the last one is working with other humans, the human-to-human interaction skills.
06:43And so we're focused on a couple of those things with our folks.
06:46And I do think those are AI-proof.
06:48I think maybe they're even AI-enabled as we think about it.
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