Wall Street Journal Describes How AI Will Eat McKinsey’s Lunch

Even thought the Wall Street Journal has “oh so reasonable” quotes from McKinsey spokescritters as to how “The Firm” is adapting to AI, the headline suggests otherwise: AI Is Coming for the Consultants. Inside McKinsey, ‘This Is Existential.’ The article has McKinsey officials make the key concession, that AI can replace a fair bit of what McKinsey has been doing, and the firm is working hard to find ways to incorporate AI.

However, the article does not hone in on the nature of the danger that AI poses to McKinsey, which is not to the need for expert assistance. Much of the work firms like McKinsey does involves non-public and often generated-during-the-study information and hence will be outside LLM text-hoovering. It is to the entire professional firm model. Its economics depend on substantial mark-ups of non-parter billed time over their cost.¹ So the fact that clients will expect a smaller engagement team to answer a question, say, “How do we improve the profits of our European operations?” than before is very likely to dent profits. That’s even more important than you might think, since pay to partners is a big McKinsey recruiting point. Less lucre puts consultants like McKinsey at a further disadvantage relative private equity and Wall Street in recruiting and retaining staff. That in turn strikes at the very heart of McKinsey’s brand premise, its eliteness.

On top of that, unlike the dot-com era, where there was an explosion of corporate demand for professional advice to help cope with this Brave New World, McKinsey is not getting enough of a demand uplift to offset the impact of the AI expectation, that McKinsey deliver more with a lot fewer people, as in lower billings. The Journal tells us, “Advising on AI and related technology now makes up 40% of the firm’s revenue” which I suspect is as broadly defined as possible so as to make McKinsey sound as if it is at the bleeding edge. The piece even mentions that McKinsey has already shrunk its headcount from 45,000 in 2023 to 40,000 now.

Back to the impact of AI on the economics of consulting firms. Professional service firms typically bill out non-owner professionals at 3 times cash compensation or ~2.4 fully loaded costs (again this is dated, with fewer vacations and sick days but more costly health care, the typical “fully loaded” level may have changed). In my day through the 1990s, McKinsey seemed to hew to this norm.

Note that there are two ways to achieve “leverage”. One is the markup of non-profit-participant time. The other is the number of juniors compared to partners. Three juniors on average to each partner-type is a lot less leverage than a dozen juniors to each partner.

And McKinsey partners are acutely aware of the importance of leverage. I was retained by McKinsey after I had left the firm to work on a project to sell a money management firm. It was clear that either the senior or the second-tier partner would need to travel internationally and spend face time with prospective buyers. The senior partner grumbled in front of me to the junior partner: “This will be unlevered time. We need to bill accordingly.”

A story will show how these economics relate directly to McKinsey’s eliteness.

In the stone ages, MBAs were rare and only a few programs had much credibility in Corporate America (Harvard, Stanford, Chicago, and Wharton; the rest were as late as the early 1980s seen as a notch below, save perhaps Columbia and NYU for Wall Street jobs). So McKinsey merely by virtue of having top school MBA (who were also often the graduates of elite colleges) could field a team that had the psychological intimidation factor of meeting with client executives who (in nearly all cases) would never have been hired by McKinsey. McKinsey did also have a track record of being a propagator of new corporate practices from as early as the 1930s.

In the 1980s, when Wall Street profits and pay levels exploded, McKinsey found that it was losing out in B school and campus recruiting for top candidates far more often than it had in the past to the likes of Goldman and Salomon. Even worse, a decent number of mid-career McKinsey professionals were leaving the firm to go to finance firm for 50% to 100% increases in pay. This was particularly destructive since those 3-6 years employees were engagement or senior engagement managers and were the working oars of the firm.

In 1987, I was brought in as one of only two non-tenured partners to assist three very senior directors, Carter Bales, Fred Gluck, and Don Waite, all of whom were contenders in the upcoming election for firm Managing Director (Gluck later became Managing Director). The other participant was Purnendu Chatterjee, then a non-tenured partner (aka “principal”) who left McKinsey to run a fund for Soros and now has his own investment firm). They had teamed up to address the question of what to do about the losses in “talent” that McKinsey was suffering. They deemed this to be so important that they did not want to tout different approaches in their campaigns but to agree on what to do to help the firm cope.²

The result (as I was told later) was that the firm decided the way to compete was to raise partner pay, and in a marked way someone “made partner” as in was elected to principal, which then was at the five and a half to seven year mark.³ The way the firm made the money math work was to increase the size of the personnel pyramid under the directors and principals, by more leverage of each partner (more juniors per senior) via staffing on studies and by lengthening time to principal and director.

The article mentions the current leverage level but in such a way that it’s still a bit opaque. From the Journal:

Traditionally, a strategy project with a client might require an engagement manager—essentially, a project leader—plus 14 consultants. Today, it might need an engagement manager plus two or three consultants, alongside a few AI agents and access to “deep research” capabilities, Smaje said. Partners with decades of experience might prove more indispensable to projects, in part, because they have seen problems before.

In my day, there were two levels of “manager”: an engagement manager (someone with at least 2-3 years of experience) and a “senior engagement manager” which would typically come at more like the 4+ year mark.

An engagement manager would lead 2-4 people, which would be a combination of more junior consultants and analysts (college grads).

It would only be a senior engagement manager that would have been in charge of a team as big as 14, and then with some engagement managers supervising the typical 2-4 professional on discrete pieces of work.

One person supervising 14 people with no intermediate minders is a train wreck, quality-wise.

In keeping, by the early 2000s, I was regularly hearing complaints from top search firms (the sort that does CEO/C-level searches) that the quality of McKinsey work had declined and was regularly out of line with the price. The same search firms were also often describing McKinsey as arrogant and aggressive, something that would have been unheard of with clients in my era, even by the most full-of-themselves directors. McKinsey was often selling (in my day, they instead marketed a ton and relied on referrals and follow-on work to generate their business) and seemed to be inept about it. I heard this sort of account more than once:

McKinsey professionals call on possible or even current client executives. They pitch a particularly engagement: “We think you should hire us to do X and here’s why.”

Client politely says they don’t think they need X done, or alternatively, they can handle X on their own.

McKinsey team gets aggressive: “No, you really need us to do X.”

This combination of factors no doubt contributes to the overwhelmingly negative comments about McKinsey in the Journal’s comment section, even before factoring their rap sheet of ethical lapses, including Enron, Purdue Pharma, UnitedHealth, cuts in patient service at NHS, bribery in South Africa, a Twitter crackdown in Saudi Arabia that may have played a role in the bone-sawing of Jamal Khashoggi.

Some excerpts from the Journal’s article:

Companies pay dearly for McKinsey’s human expertise, and for nearly a century they have had good reason: The elite firm’s armies of consultants have helped generations of CEOs navigate the thorniest of challenges, synthesizing complex information and mapping out what to do next.

Now McKinsey is trying to steer through its own existential transformation. Artificial intelligence can increasingly do the work done by the firm’s highly paid consultants, often within minutes.

That reality is pushing the firm to rewire its business. AI is now a topic of conversation at every meeting of McKinsey’s board, said Bob Sternfels, the firm’s global managing partner. The technology is changing the ways McKinsey works with clients, how it hires and even what projects it takes on.

And McKinsey is rapidly deploying thousands of AI agents. Those bots now assist consultants in building PowerPoint decks, taking notes and summing up interviews and research documents for clients. The most-used bot is one that helps employees write in a classic “McKinsey tone of voice”—language the firm describes as sharp, concise and clear. Another popular agent checks the logic of a consultant’s arguments, verifying the flow of reasoning makes sense.

Sternfels said he sees a day in the not-too-distant future when McKinsey has one AI agent for every human it employs.

An aside: I am a little surprised about the “McKinsey voice” part. How much “voice” is there in slide presentations? Again, in my day, where that showed up was proposals (written by partners) and articles in McKinsey publications, where McKinsey’s very skilled editors would whip a draft into shape. I was just about the only person evah to write a “progress review” as a text document (with charts and images in the text as well as in appendixes) in what was called “final report” format.⁴ Or are young consultants these days so poor at writing generally that they need AI to produce professional-sounding e-mails?

Mind you, AI will not kill consulting but it seems clear a lot of adaptation is in store for McKinsey and its big brand-name competitors, Bain and BCG⁵:

One immediate change is that fewer clients want to hire consulting firms for strategy advice alone…

Companies, [Nick] Studer, [CEO of Oliver Wyman] added, “don’t want a suit with PowerPoint. They want someone who is willing to get in the trenches and help them align their team and cocreate with their team.”

At McKinsey, Sternfels is trying to cement the notion that the firm is a partner, not adviser, to clients. About a quarter of the company’s work today is in outcomes-based arrangements: McKinsey is paid partly on whether a project achieves certain results.

Perhaps I am being unduly negative, but I see a lot of whistling past the grave here. Clients will expect much smaller and more senior-heavy teams, which throws a wrecking ball into how McKinsey generates enough revenue to produce the lofty pay to which its top brass has become accustomed.

Moreover, “smaller and more senior” increases the viability of boutique firms as competitors.

It also means that the ability to develop or access non-public information will become more valuable. A colleague who was an executive at an expert network firm that had two of the top three consulting firms as clients noted:

Expert networks will continue to be relevant to these firms. A useful function of expert networks that will not be replaced by AI is finding people who can offer the kind of on-the-ground perspective that doesn’t always make it into formal research or the business literature. These people provide information that is not secret, but not public. In that consulting firms are presumably paid to find and fix problems that have been overlooked, it is a relevant function in that AI simply scans information that is already public.

This “not secret but not public” information is far more widespread that one might think, and is particularly valuable to companies trying to enter a new market or second-tier players. In my day at McKinsey and after I started my own practice, I spent a substantial amount of my time generating that sort of information.

The expert network exec felt compelled to add:

I have noticed that a lot of people are treating AI-scanned documents as the letter of the law. I recently observed that the version of a law offered by ChatGPT was not only not up-to-date, but that the revised version of that law was already more than 15 years old and easily found on the Internet. I happened to be familiar with that law and its revision, but the person who sent me the GPT-regurgitated version was not. It was slightly disturbing that initially, I got a reflexive argument about it from a well-educated professional.

AI will absolutely not obviate the need for fact-checkers versed in solid research practices, if only to combat the widespread and questionable tendency, which I first observed when Wikipedia was newer, to treat Internet resources in the same manner as traditional sources.

Pundits, journalists, and our readers (particularly IM Doc!) have offered similar warnings about glaring errors in AI results, which nevertheless are too often fed into decision-processed despite that. How bad the information pollution becomes before clean-up or prophylactic efforts are made is anyone’s guess.

By contrast, it seems a safer wager that McKinsey will find it hard to preserve its current stature and profit level.

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¹ Keep in mind that even though the man who built McKinsey, Marvin Bower, modeled it on law firms, McKinsey does not provide periodic invoices of actual time expenditures, billing rates, and expenses. The practice in my day, and I doubt it has changed much, is that McKinsey engagement letters would identify the top members of the engagement team (as in the so-called Director of Consulting Services on that project, plus the non-tenured “partners” on it (recall that McKinsey is not a partnership) which then were called Engagement Directors. It would then give the size of the team that would work under them and the billing rate per month, plus the expense percentage assigned (again in my day, 15% for domestic engagements and 25% for international).

The result too often was that studies were “undernegotiated”, that the partners had promised the client too much in relation to the size of the team, which resulted in the worker-bees putting in backbreaking hours. The result too often was that promising consultants on those assignments resigning after they had landed a new job.

Mind you, the dot-bomb era led to a collapses in demand for consultants. McKinsey’s headcount in its North American offices was reduced by 50% over two years. So McKinsey may have also wound up shifting its engagement terms since my day, and particularly as a result of this huge demand downdraft.

² It was immediately clear that these three had never been in a room together without much in the way of other adults present. The jousting was impressive to behold. I kept my head down and (without having been asked) gave them a primer on Wall Street economics, describing them by major line of business.

³ If a consultant did not make partner in that window, the firm had an “up or out” policy, much like law firms for associates who do not make partner.

⁴ I was shocked when I came to McKinsey from Goldman to see that clients accepted mere sideshows as the end product, since in six months, the client would have large gaps in the information conveyed. I insisted on putting a disclaimer on all of the front pages of my progress reviews something like “This is not a complete record of the presentation” (this was actually in the firm’s lexicon but bizarrely rarely employed). I was used to professional documents being in text, such as memoranda from our counsel, valuation letters, and analyst reports, for the avoidance of doubt, as the lawyers would say.

⁵ Bain will probably fare the best. First, it has a ton of captive business from its private equity fellow traveler Bain Capital for due diligence on possible investments. Second, Bain has always worked in a very hands-on way, sending in large teams to act in a managerial capacity. How that works from a liability standpoint of the company subject to a quasi-Bain takeover is beyond me