I was looking at a leaked invoice the other day from one of the major strategy firms, and the line item for a single three month feasibility study was two point four million dollars. For a slide deck. It makes you wonder how we reached a point where the most expensive thing a corporation can buy is a PDF full of charts and bullet points. It is the ultimate PowerPoint industrial complex.
It is the ultimate manifestation of the knowledge economy, or at least what the knowledge economy used to be before the floor fell out. Today's prompt from Daniel is pushing us to look under the hood of that entire machine. He wants to know about the history of management consulting, the role of the Big Four, and how this whole junior analyst labor model is surviving, or not surviving, the current AI shift. It is a fascinating look at how institutional trust is actually manufactured and sold. I am Herman Poppleberry, by the way, for anyone joining us for the first time.
And I am Corn. You know, it is funny because when people hear management consultant, they either think of a genius coming in to save a dying company or a guy in a suit who steals your watch to tell you what time it is. But there is a very specific historical line from the factory floor to the modern boardroom that most people ignore. We are currently in March of twenty-six, and the irony is that these firms are making billions selling AI transformation to their clients while their own internal business models are being cannibalized by the exact same technology.
The roots go back further than people realize, specifically to the late nineteenth century and a guy named Frederick Winslow Taylor. He pioneered what we call scientific management. Before Taylor, work was mostly seen as a craft or an art. You did it the way your father did it, or you just figured it out as you went. Taylor brought a stopwatch to the Midvale Steel Company. He literally timed how long it took a man to shovel coal and then recalculated the optimal shovel size and movement to maximize output. He called it the one best way. That was the birth of the efficiency expert.
So the first consultants were basically just guys with stopwatches making sure laborers werent slacking off. It was very mechanical, very physical. It was about the body, not the brain.
It was entirely mechanical at first. But as the American industrial machine grew more complex, especially after the world wars, the focus shifted from the shovel to the organization itself. You had the rise of firms like McKinsey and Company in the nineteen twenties. James McKinsey was a professor of accounting who realized that companies didnt just need better shovels; they needed better budgets and better structures. He treated the entire corporation like a giant machine that could be tuned for performance. This was the transition from efficiency to strategy.
That is where the strategy versus execution divide started, right? Because today, we have this massive distinction between the strategy firms like McKinsey, Boston Consulting Group, and Bain, which we call the MBB, and then the Big Four accounting firms. Daniel asked who those Big Four are, so let us lay that out clearly for the listeners.
The Big Four are Deloitte, PwC, EY, and KPMG. Collectively, they employ over one point five million people globally as of early twenty-six. That is a staggering amount of human capital. But their origin story is completely different from the strategy guys at McKinsey or BCG. The Big Four started as auditors. Their job was to look at a company's books and say, yes, this is accurate, and no, they are not hiding money in the walls. It was a business built on regulatory necessity and trust. You have to have an audit to be a public company. It is the law.
But auditing is a low margin, high stress business. You are basically a glorified hall monitor. At some point, these firms looked at the clients they were auditing and realized they could make way more money telling those clients how to run their businesses instead of just checking their math. They realized they had the ultimate inside track.
That is the pivot that defined the last forty years of professional services. If you are already inside a Fortune five hundred company auditing their taxes, you see everything. You see where the inefficiencies are. You see the messy data. You see the skeletons in the closet. So, you offer to fix it. This led to the massive consulting arms we see today. But it also created a massive structural tension. How can you objectively audit a company's financial health while simultaneously being paid fifty million dollars a year to consult on their digital transformation? It is like a doctor who gets paid more if you stay sick.
It is a massive conflict of interest. We saw exactly where that leads with the Enron scandal and the collapse of Arthur Andersen in two thousand two. For the younger listeners, Arthur Andersen used to make it the Big Five. They were the premier firm until they got caught shredding documents for Enron. That collapse was the catalyst for the Sarbanes Oxley Act of two thousand two, which fundamentally tried to force a separation between audit and consulting. It was supposed to be a firewall.
And yet, here we are in twenty-six, and the Big Four are larger than ever. They found ways to work within those regulations, often by selling different types of consulting to audit clients or focusing on implementation rather than pure strategy. But the core of their business model, and this is what Daniel was getting at with the junior analyst comment, is the leverage model. It is the pyramid. This is the part that people really need to understand to see why AI is such a threat.
This is the part that fascinates me. If you hire a top tier firm, you think you are hiring the silver haired partner with thirty years of experience. You see him in the pitch meeting, he looks like he stepped out of a movie, he is very reassuring. But that partner is only there for the pitch and the final presentation. The person actually doing the work, the one digging through your spreadsheets, building the models, and staying up until four in the morning to format a slide, is a twenty-four year old who graduated from an Ivy League school six months ago and is working eighty hours a week on five hours of sleep.
The economics of it are brutal and brilliant. The firm hires these high achieving kids for, say, one hundred and fifty thousand dollars a year. They then bill that kids time out to the client at five hundred or even one thousand dollars an hour. If that analyst works three thousand hours a year, the firm is making a massive multiple on their salary. One partner might oversee three managers, who each oversee ten analysts. That is where the profit is. It is a labor arbitrage business disguised as a brain business. You are selling the sweat of twenty-somethings at a massive markup.
It is basically a high end apprenticeship where the client pays for the training. But it works because of the brand. When a CEO presents a plan to the board of directors, saying, I think we should lay off ten percent of the staff, it sounds cold and personal. But if he says, McKinsey has conducted a six month study and recommends a ten percent workforce optimization, it carries the weight of institutional authority. It is corporate insurance. You are paying for the name on the cover of the deck so you dont have to take the blame if things go wrong.
That insurance aspect is key. If the plan fails, the CEO can say, hey, we hired the best in the world and followed their advice. You cant fire me for following the gold standard. But this whole model is hitting a massive wall right now because of the shifts we are seeing in twenty-six. We talked about the evolution of agencies back in episode six hundred sixty-seven, and consulting is facing the same existential crisis. If the value of a junior analyst was their ability to synthesize information, build slide decks, and run basic financial models, what happens when an AI can do all of that in thirty seconds for the cost of a few cents of compute?
That is the trillion dollar question. I was reading a report that suggested the average junior associate at a major firm spends sixty percent of their time on tasks that are now fully automatable. Research, data cleaning, formatting slides, summarizing meeting notes. If you remove sixty percent of the work, the pyramid collapses. You dont need ten analysts per manager anymore. You might only need one who knows how to direct a swarm of agents. The entire middle of the pyramid is being hollowed out.
It changes the entire value proposition. We are moving from what I call knowledge arbitrage to implementation arbitrage. In the past, the consultant knew something you didnt. They had the benchmarks. They had the proprietary frameworks. They had the data from fifty other companies in your industry. Today, most of that knowledge is commoditized. You can ask a high end reasoning model to apply a Porter's Five Forces analysis to a mid sized retail chain and get a decent result instantly. The new value isnt in the thinking; it is in the doing. It is in the actual integration of these systems into a messy, human organization.
But consultants have always been notoriously bad at the doing. That was always the knock against them. They give you a beautiful deck, they tell you what the future looks like, and then they leave you to figure out how to actually change the culture or install the software. They are the architects who never actually see a construction site. Are you saying they are being forced to actually get their hands dirty now?
They have to. In twenty-six, clients are getting smarter. They are tired of paying for research they can generate themselves with a custom GPT. They want outcomes. We are seeing a shift where firms are being hired to actually build the AI workflows they are recommending. They are becoming more like high end engineering and integration firms. If you look at the hiring trends, the Big Four are hiring fewer MBAs and more data architects, prompt engineers, and systems integrators. The era of the generalist MBA who can talk about anything but build nothing is ending.
It is a weird irony though. These firms are out there selling AI transformation to the world, telling everyone else their jobs are going to change, while they are desperately trying to figure out how to keep their own billing rates up. If I can do a project with two people and an AI instead of twenty people, I cant bill for those eighteen missing bodies if I am still charging by the hour. The hourly billing model is a direct incentive against efficiency. It is a suicide pact with the past.
That is the tension that is going to break the industry. The hourly model is a relic of that Taylorism we talked about earlier. It made sense when human time was the only variable. But when compute replaces labor, the hourly model becomes a race to the bottom. The smart firms are pivoting to value based pricing. They are saying, we will charge you five million dollars to increase your margin by two percent using this specific AI implementation. If we do it in a week or a year, the price is the same. But that requires a level of confidence and skin in the game that most consultants have traditionally avoided. They liked the safety of the advisory role where they werent responsible for the results.
You mentioned something earlier about auditing that I want to circle back to. How does the auditing side of the Big Four handle this? Because you cant exactly have an AI audit another AI without some serious human oversight, right? Or can you? If the audit is the foundation of trust in the markets, what happens when the auditors are using the same black box tools as the companies they are auditing?
Auditing is actually where the most interesting, and perhaps most conservative, shift is happening. The regulatory environment, especially here in the US and in Israel where Daniel is, still requires a human sign off. You need a partner to put their license on the line and say, these books are clean. But the process of getting there is being totally overhauled. Instead of sampling ten percent of transactions to look for errors, which was the old way, firms are now using neural networks to scan one hundred percent of transactions in real time. They are looking for patterns of fraud that a human would never see.
So the audit becomes a continuous process instead of a once a year panic where everyone stays in the office until midnight for three weeks.
That is the direction. It becomes a persistent layer of oversight. But that creates a new problem for the business model. If the audit is automated, the Big Four lose those thousands of hours of junior staff work. They are currently lobbying for new types of audit requirements to fill the gap. Things like AI safety audits, algorithmic bias audits, and ESG reporting. They are essentially trying to invent new things that require their stamp of approval to replace the billable hours they are losing to automation in traditional accounting. It is a constant search for new things to certify.
It is the same old game, just with different buzzwords. They are moving from scrolls to SQL, as we discussed in episode eight hundred sixteen, and now they are moving from SQL to synthetic reasoning. But the goal is the same: to be the gatekeepers of institutional trust. I think people underestimate how much of the global economy relies on the fact that a Deloitte or a PwC signed a piece of paper. Without that, the gears of capital markets would grind to a halt because nobody would trust the numbers. It is a regulatory moat that is almost impossible to cross.
That is the moat. It is not their brilliance; it is their brand and their regulatory capture. But that moat is being tested by the transparency that AI brings. If a mid sized company can use an open source model to perform a shadow audit of their own books and find the same things the Big Four found, they start to wonder why they are paying millions for the official version. They start to see the man behind the curtain.
There is also the political angle to this. These firms are deeply embedded in the administrative state. They are the ones who often write the white papers that become the basis for new regulations. They are the consultants to the governments that regulate the companies they consult for. It is a perfect circle of influence. In a more deregulated environment, which we are seeing a push for in many sectors, that gatekeeper role starts to look more like a tax on productivity than a value add.
It is a very pro American, pro market view to say that we should be stripping away these unnecessary layers of intermediation. If you look at it through that lens, the disruption of the consulting industry is actually a massive win for the economy. We are freeing up some of the smartest minds from top universities who were previously spending their twenties making PowerPoint slides. Imagine if those one point five million people were actually building products or solving engineering problems instead of just advising others on how to do it. The brain drain into consulting has been a real drag on innovation for decades.
It really has. It is the default path for people who are smart but dont know what they want to do yet. It is basically grad school that pays you. But if that path is no longer lucrative because the entry level work is gone, those people have to go elsewhere. They might actually have to start companies or go into fields that produce tangible value. We might see a renaissance of actual engineering because the easy path of consulting has been disrupted.
I think we are going to see the rise of the elite boutique firm again. Small teams of true experts, maybe three or four people, who use a massive AI stack to do the work that used to require a team of fifty. The prestige will shift from the size of the firm to the specific expertise of the individuals. The era of the giant factory of analysts is ending. If you are a client, you dont want the factory; you want the three people who actually know how to solve your specific problem.
So, what does this look like for the person hiring a consultant today, in twenty-six? If I am a director at a tech company and Daniel sends me a proposal from a firm, what am I looking for to know if they are actually worth it? How do I separate the AI-washers from the real deal?
You have to look past the methodology. Every firm has a five step process with a catchy name. That is just marketing fluff. You need to ask about their proprietary data and their specific AI stack. Are they just using a generic GPT five or Claude four wrapper, or do they have something that actually integrates with your specific industry data? And more importantly, you have to ask for the outcome. If they wont agree to a success fee or some kind of performance based metric, they are still living in the nineteen nineties. You want a partner, not a vendor of slides.
I would also ask who is actually doing the work. If the partner tells you they have a proprietary AI agent doing the heavy lifting, ask to see the logs. Ask how they are validating the synthetic output. Because the biggest risk right now is what I call AI washing in consulting. Firms are just using LLMs to generate the same old generic advice, but faster and cheaper, and still trying to charge the old prices. They are trying to capture all the productivity gains for themselves instead of passing them to the client.
It is the agency evolution all over again. The firms that survive are the ones that become AI native. They dont just use the tools; they redefine their entire structure around them. That means getting rid of the pyramid. It means a flatter organization where everyone is a high level strategist and an operator. It is a much harder business to run because you cant just hide behind a brand. You have to deliver actual, measurable value every single day.
It also means the end of the trusted advisor being a human only role. I can see a future where the board of directors has an AI seat that has been trained on the entire history of the company and the industry, and its job is to provide the counter-perspective that a consultant used to provide. That is a terrifying thought for McKinsey, because an AI doesn't have a career to protect. It doesn't care about getting the next contract. It can be more honest than a human consultant ever could be.
Human consultants are incentivized to tell you what you want to hear, or at least to tell you that you need more consulting. An objective, localized model doesn't have that bias. It just gives you the data. But that brings up a great point about the second order effects. If the junior analyst role disappears, where does the next generation of partners come from? Consulting was always a career where you learned by doing the grunt work. If the AI does the grunt work, how do you gain the intuition and the experience to become a senior advisor? We are facing a massive apprenticeship gap.
We see that in medicine, law, and software engineering too. It is the twenty-six productivity paradox we discussed in episode eleven hundred sixty-seven. We are getting more efficient in the short term, but we are hollowed out in the long term because we arent training the next generation of experts. If you never had to build a financial model from scratch because the AI did it for you, do you really understand the levers of the business? Probably not. You just know how to read the output.
It is like learning to drive with a self driving car. You might get to the destination, but you dont know how the engine works, and you certainly cant fix it if it breaks. The consulting firms that figure out how to train people in an AI-first world are the ones that will still be around in twenty-forty. They might have to create simulated environments or forced manual labor periods just to make sure their people actually understand the fundamentals. It is a strange world where we might have to pay people to work less efficiently just so they can learn.
It is the price of maintaining human expertise. For Daniel, and anyone else looking at this space, the takeaway is that management consulting isn't dying, but its skin is being shed. The Big Four will survive because they are too big to fail and too embedded in the law, but they will look like software companies within five years. They will be selling platforms and certifications more than they are selling hours.
And the strategy firms will either become elite think tanks or they will disappear into the background noise of automated business intelligence. It is a wild time to be in professional services. You have to be faster than the model but more insightful than the partner. Which is a very narrow tightrope to walk. But it is also an opportunity for the people who actually enjoy the work of solving problems rather than just the prestige of the title.
If you are a client, the power has shifted back to you. You have the tools now. You only need the consultant when the problem is so unique or so human that the model cant touch it. Which, let's be honest, is a lot less often than the consultants want you to believe. Most business problems are not unique. They are just variations on a theme that has been played a thousand times before. And AI is very, very good at recognizing themes.
That is the ultimate commoditization of the expert. It turns out that a lot of what we thought was high level strategy was actually just pattern recognition. And we have built the ultimate pattern recognition machines. We have automated the executive summary.
Well, I think we have thoroughly deconstructed the PowerPoint industrial complex for one day. If you are sitting in a cubicle at a Big Four firm right now listening to this, maybe it is time to start looking at those internal AI tools and seeing how you can use them to do your job in four hours instead of forty. Just don't tell your manager, or they will just give you ten times more work.
Or better yet, use that extra time to build something of your own. The leverage has shifted. You don't need the firm's brand as much as you used to if you have the right stack and the right insights. The individual has more power now than at any point since the industrial revolution began.
A very entrepreneurial way to end it. I like it. Thanks to Daniel for the prompt. It really forced us to look at the plumbing of the corporate world. It is messy, it is expensive, and it is changing faster than the people in charge want to admit.
It is always good to look at the history to understand why the present feels so chaotic. We are just in the middle of a massive re-tooling of how human organizations function.
Thanks as always to our producer Hilbert Flumingtop for keeping the show running smoothly behind the scenes. And a big thanks to Modal for providing the GPU credits that power our research and generation pipelines. This has been My Weird Prompts.
If you found this dive into the history of consulting useful, a quick review on Apple Podcasts or Spotify really helps other people find the show. It is the best way to support us and keep these deep dives coming.
Find us at myweirdprompts dot com for the full archive and all the ways to subscribe. We will be back soon with another prompt from Daniel.
Goodbye for now.
See ya.
