The mbaMission Podcast
Welcome to the mbaMission podcast, where every week we discuss different MBA application components and give our expert guidance on everything business school admissions related.
The mbaMission Podcast
Ep 80 | The Impact of AI on Business School and MBA Careers
Artificial intelligence is reshaping how we think, work, and lead. If you're thinking about earning your MBA, AI is likely on your mind. In this week's episode of the mbaMission podcast, Harold Simanksy is joined by mbaMission Managing Director Harshad Mali and Executive Director Katy Lewis. Harold, Harshad, and Katy discuss the impacts of AI on the economy and MBA careers, the ways in which business schools are adapting to the prevalence of artifical intelligence, and whether or not MBA applicants need to adjust their application strategies due to AI. If you're thinking about business school and wondering how AI will impact your business school education, and your post-MBA job opportunities, you won't want to miss this conversation!
00:00 Welcome to the mbaMission podcast
00:51 Business education in the age of AI
05:21 AI's impact on the economy
06:33 How is AI changing MBA career opportunities?
14:19 How are business schools adapting to the impacts of AI
17:52 Digital literacy: What do MBA programs need to teach?
22:23 What MBA applicants and students should focus on
28:21 Advice for MBA applicants
30:02 The ethics of AI
33:32 How should you use AI on your MBA applications?
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I cannot imagine any person going to business school who's likely to not think AI is important. To me, AI, the ability to actually structure analyses and get data and answers to questions you could not physically do before is incredibly exciting.
Harshad Mali:I think by now every school has realized that AI is just a tool. It's not going to ingrain the kind of creative thinking that students need to succeed in business. I always say this: you either create AI or use AI. I think in two or three years' time, AI is going to be in the mainstream of things, and I've been saying this all along.
Harold Simansky:Artificial intelligence is reshaping how we think, work, and lead. And the MBA is no exception. For years, business schools sat on the sidelines as AI transformed entire industries from finance to healthcare. But now the question on everyone's mind is bigger than ever. If AI can do so much, is an MBA still worth it? In this episode of the MBA Mission Podcast, we explored the evolving role of business education in the age of machines that think. Today with Harshad and Katie, we'll unpack why schools were initially slow to adopt AI, how perceptions are shifting, and why the human factor, what we like to call HI or human intelligence, remains irreplaceable. From short-term job market jitters to the long-term demand for digitally fluent leaders, we'll examine where the MBA stands today and where it's headed next. AI might automate analysis, but it can't automate empathy, creativity, or strategic vision. And that's where the next generation of MBAs will thrive. By the end of this conversation, you'll see that the real question isn't whether AI will replace MBAs, but which MBAs will master AI to lead the future. AI has officially entered the classroom, but once viewed as a distant tech concept, artificial intelligence is now at the core of how business schools teach leadership, innovation, and strategy. In this episode, we dive into how MBA programs are reinventing themselves for the digital age, from Kellogg's pioneering MBAI program to new AI-driven courses at Booth Wharton and beyond. Joining me on today's episode is Managing Director Harsh and Molly, who has been following how top schools are weaving AI into the coursework and culture, and executive director Katie Lewis, who is working with many MBA clients working with cutting-edge AI in different industries and seeking to expand their efforts through their MBA. As AI becomes embedded in every workflow, the real challenge for future leaders is learning to connect human judgment with machine learning. This episode will give you a front-row seat to how business schools are preparing MBAs not just to understand AI, but to use it strategically, ethically, and creatively to redefine what business leadership looks like in the years ahead. Artificial intelligence, is there anything it's not changing? I feel like my dry cleaner is now using artificial intelligence, and actually he probably is. But more relevant to what we're talking about today is really how is artificial intelligence going to be changing both the jobs business school graduates get as well as maybe even the business school education itself. So very simple questions, harsh at answer them, please.
Harshad Mali:Okay, I'm gonna give it a try. So as an engineer, a lot of people ask me uh what is AI? So I want to clarify what that is. AI, in simple terms, is something that uh compresses all the human intelligence data and brings out information that uh people don't typically get. Our knowledge is based on what we learn and what we observe, what we experience, but by putting all of that together, we get AI. So AI can analyze things uh based on what has happened before, they can maybe make predictions uh on what is gonna happen, and uh they can also make things very efficient. So these are the three ways AI can help. Now, to answer your question, how is that gonna affect the MBA world and you know business schools and future MBAs? I think AI is going to definitely be a new uh revolution of sorts, just the way things have happened. Um, started with the computer, then the internet. Uh huh. The smartphone and AI is just in addition to that. I think it's going to change the landscape of business quite a bit in that it's going to uh increase, as I was saying before, the efficiency of how things are made. Things are going to be easier to do. Um that doesn't mean that uh students don't have to understand business uh uh holistically and uh the way it was set up in uh course curriculums. I think the theories of business are still relevant. Without that, you will not be able to use AI to get the best benefit out of what you do.
Harold Simansky:So that's in a nutshell. Yeah, no, that makes sense. Katie, you and I earlier were talking about the fact that something like 25% of GDP is now AI related.
Katy Lewis:Is that I don't know the percent. I know that I I think it's Goldman Sachs just said AI's added 160 billion to our economy in a couple of years. The difficulty is figuring out where AI is having effect, because as Harsh had said, it's affecting absolutely every single industry. And so there's no way to break that out in the numbers. But there's no question it's going to drive growth and business over the next few years, big time.
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Harold Simansky:No question about it. So, from that perspective, driving growth in business sounds to me like opportunities, but is that an opportunity for someone with an MBA? Or what does that opportunity look like? And how is that opportunity different from what it may have been like five years ago, 10 years ago?
Harshad Mali:Well, uh the opportunities are endless, really. Uh I think the growth comes through uh many ways, but the way AI is seeping into business is different in different uh conditions. Um there are so many different industries, so many different functions, and AI products and services are customizing themselves to adjust to what those specific needs are. So if you were to look at healthcare, let's say, um, you know, someone who's doing an MBA in healthcare or something related to that must know how AI can be useful for them. You know, someone starting like an like a health tech uh startup or something of that sort, uh must understand how that can be used. For example, you know, if you're looking at a health tech startup that maybe predicts uh disease outcomes, well, a lot of the data is already in there. Um what AI does is it collects data that then uh you know tries to connect with the results that have uh been seen with that data and then connects the dots, and then it can make predictions on what people can do. So this is just one example, but there are many other industries and functions that AI will affect. So I think it's a matter of, again, understanding business, learning business, and then using the AI systems uh to your advantage. No, no, that's really makes sense.
Katy Lewis:There's some industries where AI is both cutting jobs and adding jobs. For example, in investment banking, AI is being used that's cutting a lot of the junior analysts' jobs or doing a lot of their work so much more efficiently, you don't need all of those analysts. Um, in law, for example, I've worked with a client who's actually got so enamored of the new technology being used in law firms. In his case, it was just to monitor funds for investment firms, that he actually is going now to business school and wants to set up a legal tech firm. So, so in investment banking, although jobs are being cut in the junior analyst role, there's a whole new consulting business developing to create applications for investment banks. Same thing in law. You're losing the junior junior legal positions or making them a lot more efficient, but you're creating a whole new industry of legal applications and companies. So how that for MBAs, actually, that's in their favor.
Harold Simansky:Yes, yes.
Katy Lewis:They're likely to be on the winning side and not having to do the dull boring work.
Harold Simansky:No, I think that's right. Listen, at the end of the day, if they're cutting analyst jobs, that's not an MBA, right?
Katy Lewis:If you graduate business school, you're not an analyst. You're going up the high-runner.
Harshad Mali:A lot of the job losses that are happening right now are, you know, somewhat related to what has happened in the pandemic. But the AI bandwagon is on a slow, I would say, steady uh you know, uphill climb. Um I think what is going on is uh businesses are investing in AI. Also, AI creators are investing in AI. They have to invest in hardware. The hardware needs to be bought, stored, and cooled down, um, which means there's a lot of energy requirement as well. And uh what that has caused is uh businesses because they're spending money, they are not hiring as much. I think when AI comes into the mainstream completely, that's going to change because businesses are gonna need a lot more uh manpower to uh actually make the AI work. There will be certain jobs that will be gone. There's no doubt about that. But in the NBA scheme of things, I think there's uh silver lining on the horizon.
Harold Simansky:Yeah, yeah. And I'm just sort of trying to put it into the context of business school, business school applications. It's almost like your application has always needed to look to look beyond analyst jobs. It's always needed to look beyond associate consultant jobs or wherever it is. So now you're looking, I think, much more leadership focused, much more innovation focused than you maybe you've ever seen before.
Katy Lewis:Essentially, I think what business schools teach you to do is make decisions with judgment and achieve strategy with judgment. Basically, you need to realize that AI is one of your greatest tools. And so you need to know enough about AI to know how to use it, to constantly scan the environment, watch what your competitors are doing, watch, see, scan other environments, see if there are any comparable uses in other industries that you can use. But it's it's I actually think it's exciting. Anything that can power making better and more interesting and more complex decisions, in my opinion, is true. This makes Excel look like nothing.
Harold Simansky:Yes.
Katy Lewis:I mean, it and I I was excited about Excel. So to me, AI, the ability to actually structure analyses and get data and answers to questions you could not physically do before is incredibly exciting.
Harold Simansky:Yeah, yeah. No, listen, it reminds me of my time at Bain and Company when we had a whole staff that was just doing PowerPoint, that that essentially I would do hand draws or something and send it over to them. And wonderful people, but at the end of the day, they're not there anymore. And what I would say similar sorts of positions won't be there anymore. At the same point, I'm a better consultant now. I've actually now have the capacity to sort of free up some of that time and really do a little bit more deep thinking. Yeah.
Harshad Mali:Absolutely. I mean, the PowerPoint slides, you know, I hear a lot about consulting and how, oh, they put up PowerPoint slides and all that. Well, the good news is that that's not the case anymore because consulting firms actually do a lot of AI work for their clients, uh, bring out insights that even the clients don't have, and they're able to actually produce a lot of uh meaningful, substantial information now. And so for those who are thinking that uh AI is going to maybe take away certain uh job functions like consulting, let's say, they're completely wrong. I think they should uh think about this again. And uh consulting is just one industry, but all industries are using AI to their best uh advantage. No, no, I think that's right.
Katy Lewis:Consulting firms and investment banks or private equity firms are even using AI to do better work themselves. I mean, there's one private equity firm that has a six-person investment committee, one of the members is AI. Yes, and it's basically a database of all of their top investment committee reports. And so if you want to go before the investment committee with a new investment proposal, you have to put your report through that database, and it has a yes or no vote. A consulting firm is doing the same thing, they're putting their final reports through a similar customized database, and it points out the weaknesses of the point the report and the areas that should be strengthened. So it, you know, even if jobs are not only changing what consultants and investment bankers are doing, but they're actually changing what the firm itself is doing.
Harold Simansky:That's really interesting. And I think what we're experiencing inside business schools, in some ways, is they're slow to get that, and may hate to put it in that way, but at the end of the day, they almost felt somewhat flat-footed given how quickly AI has really advanced. And then suddenly we have maybe there's a few programs out there that are taking a little bit more seriously. But I mean, what's your impression as far as what business schools have been doing or aren't doing?
Katy Lewis:I don't really know, but I can't help but think there are a lot of new cases, at least in the Harvard.
Harold Simansky:Harvard Business School cases.
Katy Lewis:Because the professors at these schools have their fingers on the pulse of what's happening. They've been developing these cases for five years. I mean, AI is not new. So I'm pretty sure it's more in the curriculum than it's formally expressed with like a separate major or a separate program.
Harold Simansky:What could be interesting and ironic is now some of those cases are gonna be written to some degree by AI.
Katy Lewis:Well, the irony is that apparently most current Harvard students use AI to analyze their cases before going to class.
Harshad Mali:Yeah, yeah, I completely believe it. I think the case method is gonna be very crucial because human intelligence drives AI. And through the case method, um, students are going to learn to really think about the problems and come up with uh solutions that AI might not have. And their solutions actually will go into the data that feeds the AI. So uh that was the problem to begin with, in that business schools and professors especially were concerned that AI was going to disrupt their teaching and you know what they were bringing in their courses. And I think by now every school has realized that AI is just a tool. It's not going to uh ingrain the kind of creative thinking that uh students need to uh succeed in business.
Harold Simansky:No, that's right. And I think really we're seeing business schools do a few different things. On the one hand, we maybe have a Harvard Business School fully integrated in terms of actually cases around this, but by no means a particular focus. It's just sort of what's happening everywhere. At the same point, we have a Kellogg, which just created its MBAI degree. We have Booth's new AI-driven course standout. So from that perspective, I see just different ways that business schools are dealing with it.
Katy Lewis:I I would think one thing it's changing is AI is changing what you should be studying and learning in business school. I mean, one thing I would want to learn in business school right now, I'd want to definitely step up my learning about data analytics. What are the power, you know, what's what are the tools I have to manipulate AI? And I and so I think that there might be a shift in business schools towards data use and problem solving through data because of AI.
Harshad Mali:Yeah, absolutely. And the way you know schools are uh incorporating AI in the curriculums, right now it's mostly related to how uh the AI systems or uh services or apps or uh products can help them do better things in their line of work, but it's marketing, operations, um, and business schools don't have manufacturing, but even industries that you know lack that uh efficiency and way to predict things. I think that's how uh business schools are trying to bring in AI into their curriculums.
Harold Simansky:No, that makes sense. And and Katie, you frequently use the term digital real digital literacy 2.0 in terms of what this new MBA skill set may actually look like. Do we have we reached the point where business schools actually start they're the ones who are teaching data analytics? They're the ones who may be teaching like some schools teaching uh Python coding. I mean, where does this begin and end, I wonder?
Katy Lewis:The analytical skills you need are higher up than that. You need it's the judgment skills that you need. How do you use this data and what what's the analysis you want to structure? I mean, you know, it's it's you need to be aware of what the potential is for AI and then see how applicable it is. One very interesting client I worked with worked for a top venture capital firm, and he realized that the portfolio companies, he didn't feel they were up on AI. So he actually created a separate company that was basically a date, an AI intelligence company to scan the environment and bring each of those portfolio companies up to date on the AI that was rapidly breaking that they should be using. They even spun out their own AI company from that effort. So this, I think that if I were going to business school, I wouldn't want to really learn how to scan the environment. Whatever industry I was going into, I would want to be on top of what's happening in that in AI in that environment. You know, but it's very much industry specific, as Harshad said.
Harshad Mali:Yeah, absolutely. Very industry specific.
Harold Simansky:Yeah, Katie, I I have to bring in this example because I find it so fascinating. You have a client, he's working on AI spirit AI.
Katy Lewis:What was that? I have a client who is head of a very successful startup and then became a venture capitalist in AI. And he got very frustrated in Silicon Valley with the fact that most of the AI money was chasing job cuts. You know, venture capital was investing in companies that were going to get a quick return by cutting jobs using AI. And he thought that was a poor use of AI. He wanted to basically invest. Invest in AI that actually expanded human potential. And one of the areas he was particularly interested in is the whole area of human flourishing or spirit technology, which is an, you know, basically AI that helps you be in touch mentally with your emotions, or AI that helps you be in touch physically with your bioindicators. And it's bound to be a gigantic industry. And he basically went to business school to step back from work and invest thought in that subject and talk with the gurus who were working on that field, you know, before he could start his own basically AI-oriented VC firm focused on those companies.
Harshad Mali:Yeah. Yeah. And you know, in my case, I worked with clients who are working to support the maintenance of AI because AI needs a lot of hardware. Right. And uh you need to get some space in the data centers that are being built. Those data centers need uh a lot of energy. And because the hardware heats up, literally, uh, that needs to be cooled down. So there's a lot of energy consumption that is going to go into maintaining AI. And that's going to create a lot of jobs outside of what uh AI itself can uh produce. Um and that's where MBA is also coming into play because there are other industries that are spawned because of AI.
Harold Simansky:That's right, absolutely right. I had a client, actually, a wonderful guy, an engineer, working on quite honestly mundane things in big buildings, you know, fire systems, water, I mean, candidly, all sorts of plumbing issues. That was his specialty. And in years past, I wouldn't have given him much of a shot, honestly, with some of the top schools. But it turns out he was doing all of that work inside these huge data centers. He was giving, you know, and when I say huge data centers, I mean hardshed, you know this, they're miles long. It's sort of unbelievable. So suddenly, a voice like that in the classroom is far more meaningful than it was today, than it would have been 20 years ago. And suddenly it's a really a much different person who may be sitting in the Harvard Business School classroom, sort of giving their thoughts about, you know what, you can say what you want about AI, but here I am on the ground. And if I have to build these things, it's not so clear to me that we can do it right now. I think that that's really it. Absolutely. Yeah. So I used to joke with people, I wasn't concerned about artificial intelligence. I was really concerned about human stupidity. And from that perspective, I usually got a good laugh at that. And I'm gonna, in the context of our podcast, I'll turn it around a little bit and say right now, the notion of human intelligence rather than artificial intelligence becomes more and more important. So, from that perspective, what do business school students must, must, must learn now that maybe they didn't have to focus on three, four, five years ago?
Harshad Mali:Well, um, in terms of uh you know, getting into a business school, I think you have to do the same things. Uh, nothing is different. In fact, your creative creativity and ability to uh ideate things is even more important because uh the business school uh setting cannot plateau itself. Uh, you know, for AI to grow and for people to use AI, you need to be creative, create new ideas, and you know, those ideas will start uh start getting into the data, and then that data will get processed. So I would say at this point, um, not a big change. Um, how to use AI? I think there are many ways you can uh train yourself. Um, there are many online modules, courses, you know. If you're absolutely not aware of how AI works, I always say this: you either create AI or use AI. You never consume AI. You know, consuming AI for video games and things like that is not gonna help you in business school. But if you know how to use AI, um then I think that's a good start. If you create AI for the use of others, then that's even better. But then that we're getting into a different line of thinking there. So at this point, I would say if you know how AI can affect different business functions, uh, that's more than enough.
Katy Lewis:I think it's really an opportunity, I think a big opportunity area is using AI, learning how to use AI to color outside the lines. And what I mean by what I mean by that is there are ways AI can be used that are just unheard of. I'll give you a good example that really captivates this point. I worked with a client who uh in a private equity firm, and they invested in an app that essentially you could overlay over, it was four western states, entire hospital system. So they they didn't own these hospitals. They could just overlay this app with the data feeding from the hospitals. And they were able to use this app to detect drug abusers who were showing up at different hospitals to try to get a refill when their primary care doctor wouldn't have let them. And essentially what it allowed was law enforcement to find those people, keep them from this drug abuse. So you're you're talking about solving a social problem without hard facilities. It's it's literally an app that's using data in a way that's creative but serving a social good. And I think there are a lot of solutions out there like that for things we never would have thought we could ever do.
Harold Simansky:No, listen, I think that's right. And I think it really puts the punctuation mark on this notion of why someone who wants to be in social impact should go to business school.
Katy Lewis:Because the reality, yeah, if you're sitting or go into government, you can in fact I have another client right now, I'm glad you brought that up, who's a data data analyst, he's been interviewed at top schools. He actually set up for a major state their entire COVID monitoring system during COVID where they were able to actually figure out proximity, seed outbreaks, and you know, basically gear up different counties for use. So they were using real data, but they were feeding it into a program using AI. So it's it's those kinds of solutions that no one even thought was possible that I think is a real opportunity. And that's what business school people should be trained to do. You know, you're not going to learn that if you go to a data analyst school. You're gonna learn that in a school that's trying to integrate you to make change at scale, which is what the MBA is all about.
Harold Simansky:No, that's certainly, I mean, now that I think about it, that can sort of you can push that in many different ways. Again, you're a social impact world, which is notoriously somewhat insular. And one of the reasons you go to business school is to sort of get a business view of social impact and what that means. But imagine now you're laying on something else. In your team, we're learning team is the social impact person, but there is the harsh ad person who's pushing, you know, AI in all sorts of different directions. You may only think it's a business tool in some ways. Social impact people are looking for new tools and suddenly, wow, maybe artificial intelligence is more important there than it is in the world of finance or in one of the other worlds where honestly it's starting to be integrated.
Harshad Mali:Absolutely. I think the integration is uh going on a really uh slow but steady process. Uh I think in two or three years' time, AI is going to be in the mainstream of things, and I've been saying this all along. Uh, but the biggest, I would say, um benefit of AI is we will be able to do a lot more. Uh, you know, uh the ideation, the invention piece, which is uh, you know, slow right now because we're so involved in the process, that's going to speed up. And um, I think AI is gonna deliver far better inventions uh down the road. And that's uh as an engineer, I would like to think about it in that way.
Harold Simansky:No, no, I think that's right. So, Katie, as you think about advising just an MBA applicant, particularly an MBA applicant who, and and we see this all the time, who says, uh, you know, I want to talk about AI, I want to go into AI, I want to, I mean, uh what do you say to an applicant who is, you know, AI is really foreign to them. And this notion here if they're gonna grab the tail of this dragon and sort of have them taking somewhere, I mean, that must be uh somewhat of a treacherous place to step, I would say.
Katy Lewis:Well, once again, AI is a tool. So a lot depends on what industry they're trying to go into. If you're going into healthcare, for example, you want to learn how AI can be used in the different healthcare applications. I would I've had clients actually say in their application, one of the reasons I really want to go to business school is I want to continue in this industry, I want to have this kind of impact, and I need to come up to date on what's happening in AI. I want a lot of the a lot of what's starting to happen is happening in the university. So it is a good time to be back at school. I mean, I really think everyone has to be saying this about whatever they want to do. I cannot imagine any person going to business school who's likely to not think AI is important if they have any idea what's happening in AI. And so this is something everyone has to do. You can't really go into AI. You can't become an AI professional. I mean, you could if you want to go work for open AI, I have a client at scale AI. You know, it's really what are you trying to do in AI? How are you going to use AI as a tool to do whatever you're trying to do?
Harold Simansky:Absolutely. Completely agree with Katie on that one. One of the issues that AI is really dealing with right now is the ethics, the ethics of AI. And in actual fact, I see no better place to start thinking about that than business schools. So, from the perspective of if I'm a business school professor, how do I even start teaching the notion of ethics with regard to AI? How do I even start for myself thinking about ethics for AI? Is there any way to approach it that is organized, that lends itself to what is what I would say sophisticated thinking?
Harshad Mali:Well, uh, that's a very tricky question. I think ethics are going to really evolve over time on what the AI providers uh think uh is ethical or not. In the business school world, I will say this. Um the professors that I've talked to are being cautious about how they look at AI and how they um tell students and what they can do with AI, especially in their coursework. Um right now uh trying to use AI to come up with uh their class prep, which is okay. But then there's a line that you know a lot of the professors I have talked to are trying to draw, which is not to use AI on their homework or their exams. And so uh whether that falls into the ethical part or not, uh that remains to be seen. But from an academic standpoint, um the way I see it is if you really want to bring your organic thinking into business and you just use AI as a tool, then it starts with how you learn business to begin with. So to me, that is an ethical piece that business schools are not trying to uh avoid. Um so but aside from that, um in you know, in the professional realm or in the industry, um, I think that's a very different um, I say it's a very different balance. I think Katie might know more about that than that.
Katy Lewis:There are ethical issues at every layer of AI. I mean, starting with let's just take a company like Scale AI that that hires thousands of people around the world to train its database. Um first of all, you want to make sure the people you're hiring, there's a gender distribution, um ethnic distribution is becoming a big issue. There's very much a Western bias in a lot of AI databases. You also, there's been a recent article about the terrible work conditions these people are under. So there's some work labor ethic ethics issues. Um, then at the algorithmic level, you have to worry about the SKUs that are in database that can be unfairly burdening. You know, there's some credit scoring systems that that hurt certain ethnic groups. That's a big problem. Um, let me think of the other AI applications. There are actual AI apps, certainly in Chat GPT or filmmaking, where there's issues of using unlicensed materials or using materials that are copyrighted without permission. So, like anything else, ethics pervades every aspect of a of the stream, and and there people have to pay attention to those ethics issues everywhere.
Harold Simansky:No, and and Katie, just from a your more utilitarian perspective, right now business school applications are actually asking, did you use AI in your application? Harvard Business School says, Did you use it? How did you use it? And and honestly, how do you have folks answer?
Katy Lewis:Almost every well, as one of my clients said, who works in AI, he said, There's no way I can say no. I mean, I look like an idiot if I say. And I said, just be honest. If you use any kind of editing tool, grammarly, whatever, just say, Yeah. I use this all the time. But I but my story is my own.
Harold Simansky:That that's right. Listen, we, you and I, all of us together, we read many, many essays, particularly ding reviews. And I have to tell you, I know AI right away. And I know AI right away for a number of different reasons. It's not particularly original. It feels it's incredible. That's right. Exactly.
Katy Lewis:I actually you can go further than that, Harold. I I have I got a draft from a client and had that reaction. So I went online and put it through an AI checker, and it came out as 67% AI. So I called him on it and I said, Looks like AI, smells like AI. Just tell me what you want to say. And it was fine. Uh it's I don't personally mind it when a client says, okay, here's my article or my essay, and here's the version I put through Grammarly. What do you think? And I'll I'll give them my honest ability. The irony about applying to business school is the more genuine the application, the better. There are times when using AI, even grammarly, it just makes it sound too clean.
Harold Simansky:Yes.
Katy Lewis:Takes all the personality out of it. One of the other big problems we have is recommenders are are using, like McKinsey has a whole AI platform for writing recommendations. And I I talk to recommenders and I tell them that.
Harold Simansky:Yeah. Yeah.
Katy Lewis:You know, so it's really important to keep that authenticity in the picture.
Harold Simansky:Which is frequently specificity, right? AI is going to talk about very general things and the fact that Horshot helped this one client, spoke to them in the middle of the night when there was a crisis, AI is not creating that.
Harshad Mali:Absolutely. I think AI, and as we were saying earlier, I mean, it uh throws things in a very generic way. I think the life of an individual, his work, his personal life, you know, is very different. The way he or she thinks about um any topic or any anything that business schools are looking for uh can be different. What AI does is it tries to generalize things. And that's when you know admissions committees are like us, they they can understand things pretty quickly, even if uh you know applicants don't reveal that they have used or not used AI. So in my case, I always try to elicit the organic stuff out of my clients. I never encourage them to use AI. Um, and like Katie said, you know, I always try to help them bring out things in ways that they would speak. Um, you know, I always say good uh, you know, writing is good thinking, good thinking is good speaking, and you know, it's uh there's never any change, but that's what I try to focus on. And you know, thankfully, a lot of my clients do get that. Um, and those that don't, I really push them.
Harold Simansky:Yeah, I mean, listen, I had a client and it was sort of a crazy story. He didn't tell me he used AI, I knew he used AI, and I said, okay, what are you gonna do now? And he said, Well, Harold, let me throw go throw it through one of the AI checkers. I'm like, fine. For my mind, it was an experiment. So he sends it through the AI checker, 100% written by AI. And I'm like, okay, what are we gonna do now? I mean, at this point, it's his application, it's my application. Okay, let's play with it. Let's make sure that I get 0% through the AI checker. I'm like, great, let's do that. And it actually wasn't that hard to change things up. You know, a little bit more genuine voice. I mean, honestly, it wasn't that hard. And again, that's sort of what we do. And then he said, great, throw it through the AI checker. He did. We're down to whatever, 10%, whatever it is. I said, no, let's put it aside, let's see what happens. He put it aside, waited a couple weeks, he put it through the AI checker. We had not changed the essay one bit. The AI checker then tells him 100% written by AI. So at that point, I said, you know what? Don't try to outthink them. Tell me what you're going to tell me. Write that authentic story. Then who cares what AI says at that point? It doesn't matter if you're telling that genuine authentic story that no one else can tell.
Harshad Mali:Absolutely. I think AI is capturing a lot of data. So what we come up with today is absorbed in some way or the other. Exactly. And that goes into the data. And then when we check for um essays that uh you know uh pass or don't pass the AI test, you know, clearly, you know, anything we write today is going to uh show up as uh AI generated. And you're absolutely right. I think coming up with things in a very organic, original uh fashion that relates to you is more important. Yeah.
Harold Simansky:Yeah, yeah, no, definitely. Listen, the notion of AI, business school, generally business school applications, it's something that frequently people want to talk through. For that minute, sign up with us for a free 30-minute consultation with Katie, Harshad, myself, or one of the other 20 or so consultants we have here, and let's just have a conversation about that. Let me give you my thoughts. I can give you your thoughts. I want to hear how you're thinking about this because it is emerging. It is interesting. From that perspective, any last words, Harshad on AI?
Harshad Mali:Uh, my last words are don't fear AI, um, but don't consume AI. Uh fall in love, uh, but treat it with respect. And um that's pretty much it. Yeah.
Katy Lewis:Katie, any last thoughts on AI? Just be excited about it. I mean, it's like I'm sure when computers came out, people were nervous about them. They seemed unfamiliar, and then they figured out or or smartphones, then you figure out the potential. This is the same.
Harold Simansky:Yeah, yeah. A hundred years ago, 150 years ago, people thought telegrams would mean no more books. So at that point, we know how this goes. Perfect then. Well, Harshud Katie, thank you so much for speaking with me today, and this is the The MBA Mission Podcast.
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