E383:Why the Next Fortune 500 Companies Will Be Built on AI

0:00David, you're a founder and managing partner of Blumberg Capital, and you're going all in on AI agents. Why is now the right time to do that? Agentic AI is liberating us from the drudgery of mundane work. I'll give you one example. Cut and paste. How many of us do that over and over and over? And it's so mind-numbing, and it's not very productive. So the agent, the agentic worker for you, can do a lot of that kind of stuff. the logging in, the security protocols, the money transfer, it goes on and on. And that we're just at the first inning of this game. And in the next 10, 20 years, I predict that the work world will be entirely changed.

0:43There's essentially two narratives in the market about AI. One is it's going to take everyone's job and everybody will be jobless. And the other one is that there's going to be 10 times more jobs. Where's the ground truth? You talked about ground truth. That's why I started with agriculture. Most people don't know this. I think it's a fun fact. Remember, 250 years ago, 95 % of Americans worked in agriculture or the rural economy. Today, do you know what that percentage is? Less than 1%. It's about that. I think it's between 1 % and 2 % and falling. So all those people, quote unquote, lost their jobs.

1:16And yet, we produce far more food, much more nutritious, much safer, with far fewer accidents in the farm world. And that cost of food as a percentage of our worker daily wages is much lower. And we export to the many countries in the world. So we do a lot more with less. Productivity is the name of the game. Some people will lose jobs, but most likely, to say a cliche, you're more likely to lose the job, not to an AI, but to someone else who is using an AI when you're not. Dr. Alex Wisner-Groß, previous guest, said, if you're not at the table, you're on the menu when it comes to AI. So if you're not integrating AI, you're going to be disrupted by AI.

2:01I think about it in two different frameworks. There's David Deutsch's whole concept, the beginning of infinity. In this book, he argues that innovation is infinite. Why? Because every time you innovate and every time you create something new, it can now combine with everything else. So as you're creating more new paradigms, more new structures, more companies, they now have to interact in other ways and combine in new novel ways. So the theoretical limit to innovation is infinite. The second one is actually instead of going way into the future, going way into the past from an evolutionary psychology basis.

2:38Human beings for millions of years have been wired to be status-seeking and to be zero-sum when it comes to status. Therefore, if everybody can now afford a Rolls-Royce, there will be now something that's 10 times more prestigious than that Rolls-Royce. People will argue that resources themselves will become infinite. We'll see, maybe in 10, 20, 30, 40 years. But in the next 5 to 10 years, human beings are not so easily satiated in that if they check the box and they get this livable wage, they're suddenly happy, we may see what Elon Musk calls extreme abundance and revolution at the same exact time.

3:15I agree, at least in concept, that the innovation cycle is potentially infinite. The other one about human beings, I agree that human nature doesn't change very fast. Technology changes fast, human nature doesn't. But I'm not worried about status-seeking people competing for too many Rolls Royces. I'm worried about the fact that there are, for example, 700 million people on Earth that have zero electricity. There are 4 billion people on Earth that have less than four hours a day of electricity at their disposal because it's so unreliable or so costly. We have a lot of room to help the rest of the world move up.

3:53I'm very excited and I'm very optimistic about the potential because who wants waste? No one. What the agentic AI revolution offers us ahead of us in this bright future, this golden dawn to my mind, is less waste, more productivity. Any good economist will also tell you that the only way wages can rise is if the workers, the employees, are more productive. Now, if we give them tools that make them more productive, guess what? that's a wage unlock. People will become much more valuable to their employees if they're doing more work. Give them better tools, give them better machines, they can be paid more.

4:33The sewing machine example, when a person sewed everything by hand, X level of productivity, give them a sewing machine, which costs capex, capital investment, they're much more productive. They can pay more because they generate more. So there's a lot of post-modernist, neo-Marxist ideology that is getting infected in all of this stuff. I'm much more of an optimist because I think that most people want to do better for themselves and their families, not in an ego driven way, but just because they want to achieve, they want to do something meaningful and something that's meaningful and productive serves other people.

5:10So let's go from philosophy to day-to-day execution. You're specifically focused on B2B agents, which are agents that transact within businesses and between businesses. Why are you focused there? This is where huge volumes of waste occur. Let me give you one example. We just were showing this company at our LP meeting yesterday in New York. This is a company called Overview. They're based in the Bay Area. They're former engineers from Tesla. They were fascinated as manufacturing engineers by the factory floor and the defects and how to reduce the defects and how to increase the output of the factory line.

5:46And they realized that there were cameras on all the factories watching the production and trying to glean knowledge. But they improved the kind of camera, hardware improvement, semiconductor, we talked about that. And they improved the AI. And they put the AI with the computer vision. And they took the production of this, I won't name the company, but it's a big medical device manufacturer,$100 billion value company. They make little tiny surgical rings among many other devices, the diameter of which is as thin as this card, less than a millimeter. Now, when they're producing them, they have to look for the defects because you can't have a defective surgical ring if someone might die.

6:26So they used to be able to produce 10 ,000 a day because the inspection, the quality control was very demanding and slow and painstaking and often manual. move forward with smart, intelligent cameras, they're able to increase the production to something like 166 ,000 a day, 16.5-fold increase. And they improve the quality so that the defect detection rate, which was 94%, is now 100%. So 16.5 times better volume and at least 6 % fewer defects to a point of perfection. So that's one example. and give you so many, so many more in every field we can see. So far, you said, why is B2B so interesting for agentic AI?

7:12We cannot yet find an area where agentic AI will not improve the state of play. It's interesting because one of the first real use cases of AI was radiology. Yes. So radiology, AI quickly became better than leading radiologists to tell whether there's cancer within a patient. And paradoxically, the need for radiologists, I think, went up something like 10 times because so many people were coming in and using it and the cost was being driven down. It's one of these unexpected second-order effects of AI disruption and the bringing down of costs. There's a law in economics, and it's about energy.

7:55The less expensive energy gets, the more the demand is for it. people would think, oh, if you're more productive, then you might need less. But no, if you make it more efficient, people will use more and more of it. I hear a lot about agentic AI, hear a lot about B2B agentic AI, hear about open claw and consumer agentic AI. And when I ask people personally, one-on-one, what agents they're running, almost nobody but developers are running agents. How do you reconcile? Expert calls have always been one of the most powerful ways to build conviction. But today, investors are asked to cover more companies, move faster, and do it with leaner teams.

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10:27One of our advisors, Marshall Lux, is on the board of a number of Fortune 500 type companies. And he said, David, the board members are leaning forward. They're demanding it. And it's happening two ways. It's happening from the board down with a mandate. Do this. Bring AI into our operations. We know that our competitors are doing it or they're going to do it. We have to be competitive. And it's happening from the bottom up. Often it's a precocious engineer or a particularly young person who's just been exposed to it at school. That's happening. We saw a little bit of that in the mobile phone revolution.

10:59That was more bottoms up where the top was resisting mobile phones in the office. The corporations were giving them blackberries. That's right. The employees were asking for it. You know the story. So let me just do a data set for you that I think will help explain how big this market is. It turns out that the average white collar worker, knowledge worker, somebody who works in a bank, an insurance company, a lawyer, a consultant, marketing pro, a corporate executive, all that crowd, most of us, people in the podcasting world, those folks cost the employer about$170 ,000 a year. Now,$160 ,000 of that is wages and benefits.

11:3710 ,000 is spent on software tools that we use every day, whether it's Microsoft, plus Google, plus Oracle, plus Amazon Web Services. All of that together is a software industry sells about 1.5, I think, trillion dollars a year or 1.7, and their market cap is something like 17 trillion. Okay, that's just for the software tools. Everyone's been fighting over that for 30 years, the big companies right now mckinsey says that agentic ai within a very short period i think it's within a decade is likely to disrupt transform maybe lose 57 percent of those work hours it'll be transformed from humans doing it cut and paste boring stuff to an agent doing it seamlessly, silently, frictionlessly, 24-7, and at very low cost.

12:31So that 57 % of that$160 ,000, that's about$100 ,000 of spending that's going on wages now that can be transformed into agentic agents. So that will probably compress, just like we saw print media. They used to say a print dollar turned into a digital dime. So there'll be some compression. I don't know the ratio, but I think it's safe to say that the agentic agent software market, when deployed within, say, 10, 20 years, will be two or three times larger than the existing software industry today. You're saying 20 or 30 ,000 of that will be charged to the customers and 70 ,000 will be productivity gains.

13:16Yes, sir. Yes, sir. And there will be whole new categories of jobs created, prompt engineers. That's a new kind of job. Every large corporation that I know worth its salt has a chief data officer and a whole team, and they're grabbing data. I remember the chief data officer of Walmart telling me, we will buy every kind of data that you can offer us. They want everything. It's still unclear to me how we go from today where almost no one's using agentic AI on a TAM basis and a future where everything's running agents. No one's really giving me the game plan how that breaks down over the next couple of years.

13:53I know you can't see the future, but what are some low hanging fruits on where companies are going to start incorporating agentic AI and how is that going to happen? I'm just one little story and I already have six companies that are in this, I'll call it the loop of agentic commerce and the requisite financial infrastructure that goes along with that. That's a whole new layer that needs to be built. Let me start with truly you. I sit on the board of this company since I've known you pretty much. They're based in, came a little bit later, but they're based in Vancouver, Canada, but they sell worldwide.

14:27They sell in around 100 countries on earth and they can go to many more. They are identity management experts, leaders in the world. Identity management is known by its colloquial name KYC, know your customer. This is important for onboarding, for compliance, banks, Airbnb, Stripe, Square, gambling companies, Coinbase, all these kinds of companies need to have this kind of onboarding. Are you who you say you are? Then we go to the new era, KYA, know your agent. Remember I gave you a moment ago the example where I'm going to interact with you through a third-party bank. We're each going to have agents, one or more, operating for us.

15:06How do I know that your agent is who it says it is? So this is a whole new level of identity management that needs to be addressed. Truly is in the lead among companies helping build that whole extra layer. Then there have to be a whole another set of data. And I'll give you another example. There's an amazing company called Telon AI. They are with the hairy audacious goal, the BHAG, a big heredicious goal of one click audit. Curious about online trading, but haven't taken the first step yet? You're not alone. And Plus 500 Futures is a great place to start. The futures markets are moving fast.

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18:30Run your business smarter to a square. Get started today. So imagine that. Financial audit. Financial audit. Financial data is very well structured. So it's labeled well. So it's very suitable for AI interpretation and manipulation. Manipulation in a good sense. And the future is being written right now. For example, they just had an announcement that Citrin Cooperman, a top 20 auditing firm, just purchased, I think, by Blackstone for about$3 billion, which has hundreds or maybe thousands of private company accounts that they work on, and they do audits every year. They are auditing processes one by one by one.

19:10There are probably a hundred different processes in a typical audit, something like that. And just one of them, Quality Control, already has an agent that talent has developed and is being put into production. It's already saving Citron Cooperman, one firm out of hundreds of thousands around the world, 10 % of the spending. So 1.2 million out of the 12 that they spend on quality control is already being saved. Next month in June, they're going to add a second notch to it that will save 25 % of spending. So three out of the 12 is being that's just in a couple months. This is happening very fast.

19:46So you say that many companies are not using it. I beg to differ. They're not using it a lot that you hear about on posters or billboards or maybe other podcasts, but I'm letting you in on the secret. It's happening extremely fast. And just, I'll give you the B2C example. Look at the adoption of ChatGPT. Fastest product adoption ever, I think, in human history, right? It went to like a hundred million users. Yeah, it was literally on the graph. It's up and up and up. It's amazing. So we're living in revolutionary times in a very good sense. You talked about revolution in the bad sense. I'm talking about making humans more productive.

20:23And I'll go back to, again, historical analogy, because it's hard to always understand what's happening in the present tense. But our mothers, our grandmothers, our great grandmothers used to have wash by hand before the washing machine came around. Think how much time that liberated for people, mostly women, to do better, more creative, higher productive things. So talent is automating the auditing process. Auditing is limited, but the data that it will be surfaced from this is unlimited. It's kind of that back to the infinite innovation loop. If you're an M &A banker and you have a client that wants to do an M &A deal in the middle of the year, say, what are we in?

21:02May? So May 21st, you want to do the deal. Well, usually audits are done at the end of the year. So you'd have to do a whole special audit for May. With the audit ability that Talon is doing, it enables daily reconciliation of all the numbers. They've flown from the various systems of record. They are tallied. It's all labeled. It's all structured. We can have you have a daily audit. Now, with that daily audit, the management, the corporate overseers are seeing data they would never see except maybe quarterly or annually. So they can get information earlier and they can make decisions faster. It's also going to do something very interesting for the world of credit.

21:40And this is where Truly You and Telon, two companies in the portfolio, will be able to cooperate. Telon is developing this set of data from all the accounting firm's clients. Most of them are private companies. They don't expose their data. This is not going to be in the open source world of LLMs. This is Mr. Smith's construction company, private financial information. He doesn't share that with the big LLMs. So, Telon will create this organized, daily reconciled audit ability and information database, data lake, if you will. On an opt-in basis, this construction company can share with peers and, on a blinded basis, put their information out in return for seeing what the benchmarks are from competitors.

22:30So I will see if I'm spending too much on marketing, if I'm paying too much for plywood in that example. This has never been possible before. How will Truliu use it? Truliu is the identity management company up in Canada. They are going to use that to create the world's first global credit bureau for small businesses. Public companies have to disclose their financials. So that's knowable for banks and everybody else. Private companies don't. counterparty risk is a big issue especially in international trade so Talon and Trulia together are going to create this unique irreplaceable set of data private company financials and they're gonna make it available for counterparty risk analysis and management lending it'll help increase volume of trade in the world think because you'll be able to say I want to do business with this guy because he's he's legit he's you know solid etc etc And so it should unlock some credit around the world, make more business available.

23:29So I'm super excited. There's so many new paradigms going on with AI. The CFO of Lagora on and that to create all new metrics, they created new terminology, new lingo. One thing that's not changing is what makes businesses valuable, and that is network effects. And one of the things I see the top AI companies doing is not only gathering the data, doing the processing and efficiency gains, It's building on these network effects and building moats.compound. We talk about the data flywheel that's enabled by Agentec AI. Here's how it works. Say you're a startup company and you have some data that's proprietary.

24:10You mentioned radiology. Maybe it's that. Maybe it's construction data. Maybe it's mining data. The data flywheel. And the data flywheel starts with a company that has perhaps no data or it's got some proprietary data set. The first time a user interacts with that data, as small as it is or if it's substantial, the data is increased because of the user interaction. That gets fed back in, that creates new data. That's fed back into the model. That's called reinforcement learning. The reinforcement learning improves the model. Then the model delivers better results. And then there's more users and more data created.

24:46It's a positive flywheel. So that gives a new meaning to the term first mover advantage. First mover advantage used to be talked about in network value or in brand recognition. But here it's in the fact that if you start making a data flywheel, your data flywheel is going to be earlier than the others. And it's harder for them to catch up because your data is constantly improving. And everybody comes to a rational decision. Who am I going to use? I'm going to use the person with the best model that has the best data. they feed their data and so it can compound. There you go. So that's why we're extremely excited because it seems to apply to every domain we see.

25:27And that answers the question, how do these application companies compete or defend against these large LLMs? Yes, that does. Most people think, oh, the large LLMs are going to take over everything. No, they're going to become, I think, a little bit more like AWS, Azure, and other cloud vendors. They're going to be a utility. The LLMs, they'll do a lot of things and they're great. And I want to own a lot of the stocks and so on. But I believe that there's a lot of room for proprietary data set vertical experts because the future of agentic AI is about understanding process. And process can be very complicated and often process combined with a proprietary data set is a weird animal all of itself.