AI Is Coming for the Measurers, Not the Builders

What jobs will AI replace, and which ones will become more valuable?

Matthew Prince, co-founder and CEO of Cloudflare, recently wrote an op-ed in The Wall Street Journal about how he chose which employees to replace with AI. His argument: AI is not coming equally for every role. It's coming first for the people inside organizations who measure, report, analyze, audit, manage, and process information.

In this solo episode of The TechEd Podcast, Matt Kirchner responds to Prince’s article and examines what it reveals about the future of work. Drawing on Peter Drucker’s framework of builders, sellers, and measurers, Matt breaks down why some jobs are likely to be heavily disrupted while others may become even more valuable.

The uncomfortable truth: AI may reduce the need for many traditional middle management, finance, operations, and measurement-heavy roles. But it also increases the value of people who create products, build relationships, solve customer problems, lead change, and turn technology into business value.

From sales and engineering to marketing, STEM education, data science, and applied AI, this episode explores where human talent still matters most, and what businesses, educators, and professionals need to do now to prepare for the next phase of workforce disruption.

5 Big Takeaways from this Episode:

1. Businesses need to start their AI journey now. AI is already changing how companies operate, compete, hire, and structure their teams. Organizations that have not assigned someone to understand how AI will disrupt their business, market, or institution are already behind.

2. Measurers and mid-level managers will be disrupted the most. Roles centered on reporting, processing, auditing, analyzing, tracking, and managing information are increasingly vulnerable to AI. The opportunity is not to ignore that disruption, but to become the person who knows how to use AI to do that work better, faster, and more strategically.

3. Personal relationships become more important in the AI age, not less. AI can automate parts of sales, marketing, and customer engagement, but it cannot earn trust the way people do. Sellers who understand customer needs, build relationships, solve problems, and use data intelligently will remain critical to business growth.

4. Creativity and leadership still rule the day. AI gives more people access to the same tools, but it does not replace the ability to see opportunity, connect ideas, build a brand, lead change, or execute a vision. In marketing, business leadership, product strategy, and innovation, creative and decisive people will continue to create value.

5. The future belongs to builders. Engineers, skilled tradespeople, manufacturing talent, STEM professionals, automation specialists, and applied AI practitioners are positioned to become even more important. If AI makes builders more productive, companies will need more of them, not fewer, especially in fields tied to physical AI, robotics, smart manufacturing, autonomous systems, drones, and the edge-to-cloud continuum

Resources in this Episode:

Read Matthew Prince's op-ed in the Wall Street Journal: "How I Choose Which Cloudflare Employees to Replace With AI"

Episode page: https://techedpodcast.com/cloudflare/

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Transcript

TechEd Podcast Introduction: 0:03

This is the TechEd Podcast, where we feature leaders who are shaping, innovating, and disrupting technical education and the workforce. These are the stories of organizations leading the charge to change education to rethink the workforce and to embrace emerging technology. You'll find us here every Tuesday on our mission to secure the American dream for the next generation of STEM and workforce talent. And now here's your host, Matt Kirchner.

Matt Kirchner: 0:38

Welcome into the TechEd Podcast. It is your host Matt Kirchner, all by myself this week. No guests this week, because we are going to talk about something that has been on my mind. I know it's on the minds of many, many of our listeners, and that is what is going to happen to the workforce in the age of artificial intelligence. We are going to talk in great detail about that question on this episode, and we're going to do it using an article that I read not too long ago, and I'm going to dissect that article. I'll introduce it in just a moment. Before I do, I will tell you right up front that you are likely not going to agree with everything I say in this episode. We're going to talk about some uncomfortable topics when it comes to the workforce, when it comes to who is going to keep their job, and whose jobs are going to be really, really disrupted? When and if you disagree with me, I want you to ask this question, and it's okay to disagree with me. I'm not right on anything, although everything, although I think I'm right on this one, but it's okay to disagree with me. I want you to ask yourself this question when you do ask yourself, am I disagreeing because he's wrong, or am I disagreeing because this makes me really uncomfortable? And if you're disagreeing because it makes you uncomfortable, then you're not disagreeing, you're just uncomfortable. And so think about that, because we're going to cover some pretty heady topics in this episode of the TechEd Podcast. I was reading this editorial, and it was about a little over a week ago. It was in the second half of May. As we record this a little over a week ago, and the headline of the editorial says, How I choose which Cloudflare employees to replace by AI. And then under that, it says the company has less need for middle managers, operations jobs, and other measuring positions. Now, the article is written by Matthew Prince, and Prince is the co-founder and CEO of a company called Cloudflare. We're going to talk about prints, we're going to talk about the company, and we are going to talk about this particular editorial that appeared in the Wall Street Journal. All right, let's start with what is Cloudflare. Well, we talk about here on the podcast all the time, the edge to cloud continuum, the idea that we are making more and more decisions on the edge using smart sensors, smart devices, edge computing. As that's happening, we are taking decision making from the cloud, from the fog, from control systems and networks, and distributing it on the edge. And there's a whole bunch of benefits to this, mainly related to latency, in other words, the time it takes for a computer network or a computer platform to make a decision, and secondly, the amount of bandwidth that's required to send information all over. So, as we push decision making, as we push communication in a digital sense, further and further to the edge, we are able to deploy way more devices, way more intelligence, way more artificial intelligence, because we're not slowed down by these classic challenges of latency and bandwidth. Cloudflare is one of the companies, and doing it in a huge way, one of the companies that is doing exactly this, distributing decision making to the edge. They are a$2 billion company with a B $2 billion plus company, and what they are doing is building a huge edge network, so again, the data doesn't have to go all the way back to the data center. So think about this as like all the benefits of cloud computing, but doing it at the edge where we can do it faster, doing it at the edge where it might require less energy, less computing power, and so on, and they're doing this by basically placing equipment across certain geographical areas and using third-party facilities, so they're taking basically computer processing, data processing equipment, pushing it from the cloud closer to the edge, so this is what this is what Cloudflare is doing, and super, super important to understand their business model, because it is going to continue to proliferate as edge computing continues to proliferate. Matthew Prince wrote the article. Matthew Prince is the co-founder and CEO of Cloudflare. He's got a really interesting background. He was educated at Harvard Business School before that, Chicago Law School, so he's got a business degree, he's got a law degree, worked for a couple tech companies along the way, an adjunct law professor for a while. My favorite thing that I saw in his LinkedIn profile, he is a former ski instructor in Park City, Utah, and I love the fact that he still has ski instructor here. The guy's running a $2 billion plus company still has ski instructor as one of the jobs on his LinkedIn profile. So that's Matthew Prince. We now know a little bit about Cloudflare, and let's talk a bit about what Matthew Prince had to say in this article. I'm going to do this by reading bits and pieces of his editorial, and then offering some of my own commentary on the article, and I will be sure to let people know when I am quoting the article and when I am switching over to offer my own thoughts on what Matthew Prince is saying. He starts off by saying this, and this got my attention to this first sentence of his of his op-ed, he said two weeks ago I laid off more than 20% of my workforce. I didn't do it because Cloudflare is struggling. We posted record revenue, have strong free cash flow, and are adding an unprecedented number of customers around the world. I did it because business is changing, and to win the future, Cloudflare needs to change with it. Now, this is me, not Prince. Business is changing, and Cloudflare needs to change with it, is what he says. I couldn't agree with him more, and it's fascinating for me to watch. We still got some companies, some organizations that are sticking their head in the sand, thinking that AI isn't going to be transformative, machine learning isn't going to be transformative. I would tell you that, compared to a year or two ago, we see more and more companies saying, okay, we better figure this out, but there's still companies that say, I don't think this is going to change so much, or change my business, or change my market so much. It is going to change every business, every market, and so, in the same sense that business is changing, and Cloudflare believes, at least according to its CEO, that they need to change with it. I would say that's that's advice for every single business, every single organization. Now, back to the piece, we haven't found another example in US business history of a public company growing at more than 30% that laid off more than 20% of its workforce, yet what we did is likely going to become the norm over the next year. This is a story about artificial intelligence, but executives and commentators are misunderstanding how it will disrupt business and who will be affected. So think about what he says in that first sentence of that paragraph, he said they can't find another example of a company that's growing like they are and is actually laying off one in five of its employees, can't find another example of that. Moreover, he says that layoffs like his are now going to become the norm over the course of the next year. You think about tech companies, many cases growing like crazy, growing in double digits, sometimes even more. Otherwise, successful companies, otherwise profitable companies, according to Matthew Prince, are going to be laying off more and more of their people in the near future. So, more than 20% of his workforce, is that what we're going to see in some of these successful companies? Is he right? Well, I don't know for sure, but he could be. I think the fact that we're even saying that is really, really significant. The act, the fact that we're even considering the idea that even in a growing market, even with a growing company, we'll be laying people off, we'll be downsizing the workforce, that is really, really significant. And I would agree with him. I don't know if there's another example in history or not, but certainly none that I can think of, and that is really, really unique to think about growing companies downsizing their workforce. I go back to a quote that I use quite often. It's from Julie Sweet, the CEO of Accenture, where she said last year that Accenture was exiting employees that weren't getting in the handle of using AI, or weren't getting the hang of using AI, I'm paraphrasing her quote, but you think about an organization like Accenture, huge huge consulting company, saying we are laying people off if they're not getting the hang of AI. Big, successful companies are willing to downsize their workforce, or at least cut certain positions if we're not adopting artificial intelligence. Okay, let's talk about the last sentence in that paragraph where Prince says this is a story about artificial intelligence, but executives and commentators are misunderstanding how it will disrupt business and who will be affected. This is the key. He's saying he's laying off 20% of his workforce, but he's not doing it discriminately. He is looking at what positions are affected and what positions won't be affected, and I think this is really, really important. And I think he makes a really interesting case around what positions he feels are going to be disrupted by artificial intelligence and which ones are not. He says now. And again I'm quoting Matthew Prince. He says, "To understand the issue, I went back to a book published in 1954 20 years before I was born, Peter Drucker's The Practice of Management. Drucker explores the different roles inside every business, which I would categorize as builders, sellers, and measurers, all right. So, he's quoting a guy named Peter Drucker. If you came of age in business in the last 1020, years, maybe you have no idea who Peter Drucker is. If you came of age in business, like I did in the 1990s you absolutely know who Peter Drucker is. I, in fact, I would say I won't even count the number of courses, but as I was studying business in the late 1980s instructors, teachers, professors went back over and over and over again to Peter Drucker's works. He's the father of modern management, modern leadership philosophy. He was an absolute legend. Again, back in the 1990s people talked about him all the time, and certainly before then, he wrote 39 books on the topic of management. He was all about great strategic planning, decentralizing business models, customer-centric business models. He was huge on placing the customer at the center of all of our business decisions. He was an early understand, or if that, if that's a, if that's the term of the ideas of innovation and how organizations needed to continue to innovate in the age of technology of continuous improvement, for which I've always been or long been a great, great advocate. If you've ever heard the phrase, what gets measured gets managed, or as I like to put it, what gets measured improves. If you've ever heard that phrase, you're familiar with Drucker, because he came up with that phrase. What gets measured gets managed. So that's a little bit on Peter Drucker. And in this piece, Matthew Prince is going back and saying the different roles inside of every business can be basically distilled down to builders, sellers, and measurers, so now back to the piece, back to prints. He says builders create products, sellers sell those products, measurers do everything else: internal audit, revenue recognition, finance, legal compliance, middle management, operations, and on and on. Contrary to what some analysts predict, builders aren't going anywhere. If an engineer on my team can now be 10 times as productive, I am going to hire as many as I can find. I want to reiterate that he writes, contrary to what some analysts predict, builders aren't going anywhere. If an engineer on my team can now be 10 times as productive, I am going to hire as many as I can find. Continuing with the piece, sellers too are safe from extinction. Humans still control budgets, and they want to buy from people who take the time to understand their needs, build trust, and fix whatever goes wrong. So now off of the piece, and onto my commentary. This is really interesting. What Prince is saying here, he's saying that builders, so the people in organizations that create products, he's saying that sellers, the people who build relationships with customers and take the time to understand their needs, build trust, and fix whatever goes wrong. That these two positions are going to continue to be really, really important. I think about this in some of the ed tech businesses that we own, separate from podcasts, separate from the TechEd media group, distribution companies, where we're not necessarily innovating new solutions that we're selling to customers, we might be innovating new ways of doing business, but not the solutions or products themselves, where we are not manufacturing those products, where we're not managing production, we're not managing lead times, we're not managing product quality necessarily in the distribution businesses that we're in. This is really, really important to me. I sat in a meeting 20 years ago, probably more than that, with a group of CEOs, and we had a resource specialist, a speaker that came in. One of the individuals in that group was running a distribution company, and the speaker looked the guy in the eyes and said, "If your business is distribution, your company is going to be dead in the next five years. All right, this was 20 years ago. Obviously, that hasn't been the case, companies in the distribution space are still alive and well, and they're alive and well for the reasons that the Drucker points out. He says we take time to understand customer needs, we want to build relationships, and customers want to buy from people who take the time to do that. We build trust and we fix problems when problems arise. That's what sellers do, and this is really, really important when I think about the businesses that we are in. So, I agree with Prince here. I don't think that the seller's job, the individual, whether it's technical sales, whether it's product sales, whether it's business development, I think there's still a role for those people. How they do those jobs is going to change, they're going to become. More data driven, they're going to become much more efficient in terms of how we get to customers and how we build those relationships by understanding markets and understanding our customers, but the fact of the matter is that while those roles might change a bit in terms of how we do sales and business development, the fact that we need people in those types of positions really, really important, and I agree with Prince, as I mentioned. Okay, so now back to his piece. Next paragraph, he says measures are also critical to a business, but different from the other two, the best are hard to find. They work tirelessly behind the scenes, don't seek the recognition of a front of house role, and ideally have a perspective independent from the rest of the organization. Drucker argues that measuring business is important, but customers are earned through building and selling. The best businesses would maximize investment in those two functions. Okay, so lots to unpack, even in this individual paragraph, he talks about the importance of measures, that good ones are hard to find, that they have a perspective independent from the rest of the organization, but that while measuring is important, customers are earned through the building of new products, the creation of products, the engineering of products, and the selling of those products. So, let me put this into a little context. We talk a lot in manufacturing about adding value, the concept of adding value in a manufacturing business. And when we talk about what adds value, what we mean is what is the customer willing to pay us for, what is the will customer willing to pay for, and what the customer is willing to pay for, or pay more for is what adds value, and what a customer is not willing to pay for is what we call non-value added. So, think about, think about a car, you're buying a car, people will pay more for a car if it has certain attributes, right? If a car has better acceleration, if that's important to somebody, they might be willing to pay more for the car if it has more cargo space, and that's important to them. They might be willing to pay for the car, especially in this day and age, as we record this. If a car has better gas mileage, can run more efficiently, they might be able to pay, or willing to pay more for a car. Maybe somebody with a, with a family who's, who's trucking their family around prioritizes safety, and they're willing to pay more for a car that is safer. Maybe for you it's creature comforts, maybe, maybe it's lower late maintenance, maybe it's a longer vehicle life, so more reliability. A car that's going to run longer. These are things that are valued in the case of an automobile by a customer, and so the idea goes, if it's something that a customer values, the customer will be willing to pay more for those certain attributes, and that's what we mean when we say value added. People won't pay. Let's think about what we won't pay more for a car, what attributes might not matter, or what aspects of that vehicle might not matter to us, so if a car company has more accountants to measure the performance of the company, so let's say it's GM or it's Stellantis or it's Hyundai or it's Toyota, and they've got a lot of accountants to to measure the performance of the business. As are you, as a buyer of a car going to pay more for that car because they have more accountants. Well, there might be some benefits to that that manifest themselves in the value of the vehicle that you would pay more for, but you're certainly not going to pay more for a car just because the company employs more accountants. What if they have more senior executives making million dollar salaries? Are you going to pay more for your car because the company is paying its senior executives more money, or has more of them? Are you paying more for the car? No. What about more human resource, human resources people? Again, not that those folks aren't important, but you're not, as a customer, paying more just because the employer, the company has more HR people. What if they have higher transportation costs to move their products around the country or around the globe because of their supply chain. You're not willing to pay more for that. You're not willing to pay more for a car just because they have more marketing people. Maybe they do better marketing, and so you might be willing to pay more for the car because their brand message resonates with you as a consumer, but just because they have more people sitting in a marketing role doesn't mean that you're necessarily going to pay more for that car, right. So this is what we talk about, and this is when Prince talks about the idea of types of roles in an organization that add value to the organization, and what parts of an organization don't, and he says customers are earned through building and selling, not just because we have more measures, so that's that's what the idea behind this is, is that customers are earned by adding value for those customers. Now, back to Princess Peace, he says AI isn't coming for builders or sellers, but. Is coming for measurers again. We talk about the measurers, we give some examples a little bit earlier. Those are those non-value-added people in an organization, in terms of not adding value to the customer or to the experience. So he says AI isn't coming for builders or sellers, but it is coming for measurers, tireless, independent, efficient, and available AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees. For Cloudflare internal audit previously picked a handful of business risk areas to scrutinize each quarter. Now we're moving to a system in which every business risk is audited continuously. We're closing our books faster, we're making fewer mistakes, and catching the ones we did more reliably. And as CEO, I've never had better tools to measure exactly how the business is performing, including identifying our rising stars, so what Prince is saying here is that he now gets better information, he gets more accurate information, he gets more reliable data and information using artificial intelligence, and then he used to get from people, and using not just AI, but from people using AI, utilizing AI to pre-create inference and connections and data for him, he gets more information that is accurate, reliable, and he gets it faster than he did using people. So, if you're running a company and your company relies on great information to be able to make great decisions, and you can get it faster from doesn't matter whether it's one person or another or AI or a person, and he is saying he's getting data, better data more reliably and faster using artificial intelligence in his organization than he did using people. I think that's an important takeaway here. Back to the piece, the vast majority of those we laid off last week were measurers. We cut middle managers across the organization because AI allows us to have more direct reports per manager, while still managing and mentoring our teams effectively. So, middle managers, the dreaded white collar wipeout sounds like it has arrived at Cloudflare. Now listen to what he is saying, and what he is not saying. He's not saying we don't need mid-level managers, he's saying we need fewer of them, and he's saying that we need fewer of them because AI allows us now to have more people reporting to a single manager than before, because the manager's job is being augmented by artificial intelligence, right. Think about that. The job of the middle, mid-level manager. So, in other words, you're not a senior executive, you're not a CEO, you're not a chief operating officer, you're not an executive vice president or a vice president. You're also not somebody working on the manufacturing floor, you're not somebody working on the ground in the field, you are somebody who is working in a mid-level management position. You're reporting to somebody in senior management. You have a group of individuals in the organization reporting to you, that's a mid-level manager. He is saying because those individuals are augmenting and leveraging artificial intelligence, we don't need as many of them, simply because we are utilizing AI to make those people more efficient. We'll have a message for the mid-level managers in a little bit, but, but to kind of give that, give that away. If you're a mid-level manager and you want to keep your job, you need to be augmenting your work with artificial intelligence. You need to be leveraging AI tools, you need to be leveraging GPTs, you need to be leveraging the AI platforms that your employer makes available to you if you are going to be successful in this new era of leadership. All right, now back to quoting the piece in the Wall Street Journal by Matthew Prince. We consolidated our operations functions into a single group that can support teams across the business using AI to gain specific expertise when needed. We significantly reduced our marketing team, which, like in most companies, was teaming with measurers across our finance team. We found opportunities to consolidate and automate, and this is now me, not the piece. What he's saying here is that, you know, these 20% of his workforce, this 20% of his workforce that has been eliminated came from areas in marketing, came from areas like finance, where they found opportunities to consolidate and automate. I want to dwell for a moment on this marketing angle. I think what's interesting here is where he said we reduced our marketing team that was teeming with measurers. He didn't say he cut marketing. He didn't say marketing wasn't important in the age of artificial intelligence. He said that we needed fewer quote measurers in our marketing team in the age of AI. Who are the measurers on a marketing team? Right, on a marketing team in a business, you're creating brand awareness, you're building your brand. And you're connecting with customers, you're managing social media, you're managing video content, producing all this content, you are understanding market trends. I mean, all of these things that happen in a marketing operation, these are the kinds of things that that marketing does and does well, and it's really, really important, but Who are the people that are the measures in our marketing team. When he talks about eliminating 20% of his workforce, who are these people? A lot of marketing has to do with doing things like tracking performance of marketing campaigns, understanding the flow of a lead through marketing or business development process, return on investment, measuring ROI on marketing efforts, with which personally I have mixed feelings about. That's a story for another day, but measuring return on investment, analyzing data coming from the market, analyzing data coming from the business development team, identifying trends in markets, connecting the metrics that we're seeing in marketing to the business outcomes we're looking for, tracking conversion rates of customers that are lead becoming an opportunity becoming purchase order, what we call pipeline progression in the business, measuring customer awareness, measuring satisfaction of customers, measuring market share, these are the things that our measures do in marketing, and so what he didn't say is that we're eliminating creative people. What he didn't say is that marketing isn't important. What he didn't say is we're eliminating our content creators, or our social media managers, or leaders, or the individuals who are controlling and managing and growing our brand, he did say that the measures in marketing are going away. I could give us same types of examples for a finance team, and I worked on finance teams really in my career. Same types of things, we're not eliminating those disciplines, we're not saying they're not important, we are eliminating the people inside of those disciplines that can, whose jobs can be performed more effectively, more efficiently, more reliably by artificial intelligence platforms, and so that is what he's saying in this particular part of the of the piece. So now back to prints, but the layoff wasn't about reducing headcount. In fact, we have a record number of open positions in coming years. I expect our number of employees will continue to grow with fewer people needed for measuring. We can now invest more in people in the areas that drive growth. We received almost a million applicants for 1111 paid internships this summer. The interns we hired are extremely qualified and AI native, they are all builders or sellers, and we expect the majority will get full-time offers, right? A million applicants for 11 111 paid internships this summer. I want to jump in here and just share an observation from one of our companies. One of our companies is is recruiting a data analyst right now a data scientist? I, you know, I've made a commitment that I will go the rest of my life and never own a company, never lead a company, never be part of a management team that doesn't have a full-time data scientist on staff. They're absolutely invaluable in terms of understanding markets, understanding trends, understanding engagement, all the things that are so important in an organization, but we're recruiting a data analyst in this company, not one in the traditional sense, right, but somebody who leverages data and data sets and data layers and artificial intelligence to provide what we call inference for our business, using trained machine learning models, making connections, finding patterns, and generating this is a word that I coined several years ago, generating what we call informationable data. So, how do we take data, discern what's important to the organization from what isn't, figure out what's actionable, and then act on that data? So, informationable data - it's actually a word that I copyrighted all the way back in 2017 saying this was the future of business, here we are nine years later, and it's the present of business, but I will tell you that just recruiting that one position, it is insane how many applicants we got for that job, and we're looking at how do we use even more of these types of people, people that understand data, people that understand computer science, not in the coding sense, because that's going away. We cannot code with GPTs, understanding what we're doing with code, code, and understanding how it's important, understanding how to apply it. That's still really important. Writing the code itself, less important, but understanding how we take data and create actionable information for the organization. And I can tell you, we got buried with resumes for those positions, too. So many, as an aside, young people coming out of collegiate programs in those disciplines that are looking, looking for jobs. The message for employers is, if you're not leveraging all the data you need to be in your organization, now is a great time to hire somebody with incredible talent and start leveraging the data that's available to you in your. Organization, but this is exactly the way we're looking at our businesses, as well as, as we maybe need fewer measurers, we are upscaling our team members around how do we use AI, how do we use inference, how do we use the data that's being produced by our MCP servers, model context protocol servers to put it to work in our, in our organizations. Back to the piece, Prince is referring to buyers and sellers, right? He says they're the next generation who will invent ways to drive our business. With AI, we can now better measure their contributions and accurately identify those who will be tomorrow's leaders. AI isn't the harbinger of bleak youth unemployment; it is quite the opposite. AI won't kill all jobs, but it will change every business. Ultimately, it will prove Drucker right. AI will allow us to better measure our organizations, so the humans on our teams can focus on where they create and capture value, building and selling. That again, Matthew Prince, the CEO of Cloudflare. So, why did I take this whole episode of The TechEd Podcast and, instead of having a guest on with us, analyze and dissect that entire piece? I think it's because, in a lot of ways, Prince raises some really, really interesting concepts and topics for our audience. I want to highlight five things that were my takeaways from this particular piece by Matthew Prince. Number one, the world is changing and businesses need to change with it. That's where he opens, and this couldn't be more true if you haven't started on your AI journey, and I don't care if you are an educational institution, a school district, a manufacturing company, a marketing business, an e-commerce company doesn't matter, whatever space you're in. If you haven't started on your AI journey, if you can't point to that individual who's responsible in your business and your organization for figuring out how AI is going to disrupt your market and what you should be doing about it, you need to start now. You need to find the curious people, as my friend Todd Wanick of Ashley Furniture Industry says, find the curious people in your business. As Barbara Humpton, the CEO, formerly of Siemens USA, said, if you have curiosity and initiative, the world is yours. You have to find those people in your organization. You got to start your AI journey now. In waiting a year or two, may be too late. Waiting six months may even be too late. We need to start now. Number two, measurers and mid-level managers will be disrupted the most. I started my career. I don't, don't brag about this on the podcast too often. I've mentioned it a few times. You know, a lot of times people think I came out of the technology side of a business or the operation side of business. I found my way there, but I started in financial accounting. So those types of jobs, you better start finding a way to leverage artificial intelligence if you're in the finance, if you're in the accounting department in any kind of an organization, because there's this way, it's way too easy to develop software to do analytics to produce information to summarize data using AI. Now, the individuals in those spaces that are leveraging artificial intelligence to do that work and understanding how to do it, you have tremendous value. The people that are doing accounting jobs in the traditional sense, finance jobs in the traditional senses, and as we deep dove on this particular episode of the podcast, jobs like marketing in the traditional sense, on the measurement side, gathering data and just processing data, that's all going to move over to artificial intelligence again, the creative side of marketing, understanding the brand, reaching out and connecting with customers, all that stuff stays, but the blocking and tackling stuff is going to be increasingly adopted by artificial intelligence. So that's number two, measures and mid-level managers, same thing we talked about in Prince's piece, that mid-level managers are going to be in a position where they are going to be able to do more because they're leveraging AI to help do their work, they have more direct reports, and as a result of that, it's basically simple math. If I can have more direct reports, I probably need fewer people in mid-level management. So there again, if you're using AI as a mid-level manager, if you're leveraging it, the news is probably really good for you. If you're waiting for somebody else to figure that out, maybe not so much. I think the message is pretty clear. There we need to be educating ourselves on the use of AI tools and making sure we're leading the AI change in the AI transformation in our organization, as opposed to waiting for somebody else to do it, or worse yet, becoming a victim of it. Number three, in the AI age, personal relationships become more important, not less. I love the fact that Prince talked about the whole idea that people buy from people they trust, people buy from people who can solve problems for them, right. And so we're going to get to a point where we've got agentic marketing, and where my agent is buying from your agent in an age. AI sense, I don't deny that, and I think that is coming, but I'm a huge believer in the power of personal relationships, and it's as much as I can, I can use AI as a tool, I can never genuinely trust artificial intelligence, because it's not trustworthy necessarily, it's not earning my trust, it's just a platform or a tool that I can use. People earn trust, people solve problems in the customer-facing side of business. Will remain really, really important. It is going to change. It's going to become more data-driven, as I suggested earlier. We're going to have way more tools at our disposal to find customers, to engage with customers, to solve their problems, to troubleshoot their issues using artificial intelligence, but I think on the sales side of the world this is still going to be a really, really important aspect of business. So, in the AI age, personal relationships will be more important, not less important. Hone your relationships, hone your ability to engage with other people, to build relationships and trust with them. All right, number four. In the age of artificial intelligence, creativity and leadership will still rule the day. So, the more creative we are, the more we can take our creative beliefs, understand intersections in market markets and products, understand how we can do something different, more effectively, more efficiently, more productively than others, that creativity everybody has access to the same generative pre-trained transformers. It's how we take what we're learning from them and put it to work in our organizations, and then execute, and that's what we mean by leadership. So, the ability to think creatively, to come up with new ways of doing things, and then to lead change, to execute change, to lead into the future, if you're a senior leader in an organization, if you're a mid-level manager that's understanding how your organizations can be disrupted. If you are somebody that works in the field of marketing, in the, in the field of content creation, really, really important and really, really exciting future for you. If you fall on the measure side of any of those, maybe not so much, so creativity and leadership will still rule the day in the age of artificial intelligence. And finally, number five, and I want to share a little bit of a story with you as I talk about my fifth item here. I was keynoting an event in Western Michigan a week ago as we record this, and the audience was a group of professional engineers. I used to obsess over the closings of my speech, so if I was writing a keynote and I didn't have the perfect, the perfect finishing point to send the audience back into the world fired up and ready to drive change to act on what we talked about in the meeting or in the in the presentation and in the keynote, that really bugged me, and I would obsess over them, and a lot of times I couldn't come up with the perfect finish to the keynote, and so I would like lay awake at night, and then finally figure it out, and then after hundreds upon hundreds of keynote addresses and speeches, I came to realize that the answer would always come to me before I got up on the stage, and such was the case last week, speaking to these professional engineers about artificial intelligence, about how AI was going to disrupt the world of engineering. I was about an hour before the speech, still hadn't written the close of the speech, and I was just catching up on some things. And I read the Wall Street Journal every day, reading the Wall Street Journal, that is when I happened upon this particular piece by Matthew Prince, and it became the closing for that keynote. I quoted what Prince said when he talked about builders being really, really important, that the people who create products, the people who innovate in organizations using artificial intelligence, he is doubling down on those types of people. He said, if AI can make builders more productive, and I'm paraphrasing, I'm gonna hire 10 times more of them, not less of them. And here is a message for anybody who is a builder, who are our builders. Well, it's anybody working in the skilled trades, who are our builders, is anybody working in manufacturing, who are our builders, it's anybody working in the field of stem or engineering, and this is why I'm such a huge advocate for what's happening in stem education. This is why I'm such a huge proponent of the edge to cloud continuum, and teaching it at every single level of education. This is why we talk about physical AI, this is why we talk about drone technology, this is why we talk about d scanning and d design and fabrication in autonomous vehicles. This is why we talk about things like smart manufacturing, about robotics and automation. This is physical AI, and this is the future of every single sector across the market. So, if you are in STEM education, and obviously, being the tech ed podcast, we are really, really focused on anybody innovating and disrupting the world of technical or STEM education. This is a really good time for you, if you get this right. As Prince said, the future belongs to the builders and sellers, and particularly in this case to the builders. So, invest in applied art. Official intelligence, invest in physical artificial intelligence, invest in STEM. Direct more students toward these careers. When we do that together, we will secure the American dream for the next generation of STEM and workforce talent. And, of course, that is what we are all about, and the sole reason for the existence of and here at the TechEd Podcast. So, thanks for being with us on this particular episode. As we dissected this really interesting piece by Matthew Prince, published in the Wall Street Journal, we'll link it up in the show notes. We're going to put those show notes at TechEd podcast.com/cloud Flare, that is TechEd podcast.com/cloud Flare, that is C L O U D F L A R E, when you're done there, you can check that company out on social media, but even more important, at least to me, check out The TechEd Podcast on social media. You'll find us on Instagram, we are on Facebook, we are on Tick Tock, we're on YouTube, we are anywhere that you go to find your social media, you will find the TechEd podcast, and when you do reach out and say hello, we'd love to hear from you, and love to see you again next week on the TechEd Podcast. Until then, I'm your host, Matt Kirkner. Thanks for being with us.

Unknown: 41:11

Bye.