In this episode of Making Markets, Tom Siebel, CEO of C3 AI rejoins host Daniel Newman to talk about big events in the world. Beyond C3 AI’s recent results, Siebel talks about inflation, interest, famine, and politics — and even delves into the debate on remote work and why his company is 100% in the office. This exhilarating and candid discussion shouldn’t be missed as the long-time software icon talks about what is now and what is next.
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Transcript:
Daniel Newman: The company is sitting on a billion dollars in cash. And while it is burning cash, it isn’t burning very quickly. C3 AI CEO, Tom Siebel, returns to the show to talk about the company’s stable position, amidst a wild global situation that isn’t only creating volatile markets, but unrest and distress across the globe. Eye-opening to say the least and informative for those that want to hear from one of Silicon Valley’s long time software pioneers. All right. It’s time. So, strap in for this week’s Making Markets.
Announcer: This is the Making Markets Podcast. Brought to you by Futurum Research. We bring you top executives from the world’s most exciting technology companies, bridging the gap between strategy, markets, innovation and the companies featured on the show. The Making Markets Podcast is for information and entertainment purposes only. Please do not take anything reflected in this show as investment advice. Now, your host principal analyst and founding partner of Futurum Research, Daniel Newman.
Daniel Newman: Tom Siebel CEO C3 AI, welcome back to Making Markets.
Tom Siebel: Hello, Daniel. Nice to see you.
Daniel Newman: It’s good to have you back on the show. It’s been a while since we talked last, but that hasn’t changed the fact that I’m following what’s going on with your company and the tech space at large. But what I will say is since the last time we talked, the macros have changed big time, and I’m going to want to spend most of our show talking about that. And I hope you’re going to be okay with it?
Tom Siebel: I’m really okay with it, because I think the macro, if you look at what’s going on kind of globally, it’s very disturbing. It’s very important. And I can’t understand why people aren’t writing about that more. It really doesn’t matter, I think. The front page is all about the Amber news trial and how much some tech stops dropped today. When we’re looking at the potential of famine at global scale and nobody’s paying attention to that, I don’t quite get it.
Daniel Newman: Well, one of my favorite movies is the Big Short, I’ve watched it quite a few times and I know it’s a drama and I know there’s a lot of creative liberty, but I still do love that whole part when he’s, Ryan Gosling’s character is saying, “And no one’s paying attention, their foot’s on fire.” And he is talking all that stuff and about how the whole industry, the whole world missed the fact that we had created the atomic bomb of products with the credit default swaps. And yet somehow the smartest leaders in the world had no clue it was happening. So the fact that you bring up things like famine, the fact that you bring up things that are so much larger than whatever’s happening in Hollywood, it gives me hope that maybe somebody is paying attention, Tom.
Tom Siebel: Well, I will agree with you. I think that was a very, very well produced movie. It was a great book and it was a great movie. They’re really very different. The director took a lot of creative license with the movie. He, I don’t know who the director was, but he did a remarkable job, but I mean, let’s look at what’s going on at global scale. I mean, this is like, the four horsemen of the apocalypse. I mean, we have pestilence, famine, war, death. There’s a whole picture. Right. Okay. And you got COVID, so we have these problems with potential famine this year, in some parts of the world, is really quite staggering. 30% of the world’s wheat is off the market, tradable wheat is off the market from the Ukraine and Russia. As a result, fertilizer prices from Russia, 10% of the world’s rice production will be down 10% this year. That’s 26 million metric tons. That’s enough rice to feed a half a billion people. So fast math there’s somewhere between a half a billion and a billion and a half people who don’t eat this year.
I mean, come on, let’s get a grip on this. I mean, half a billion to a billion and half people don’t eat. This is all north Africa. Okay. Egypt, Tunisia and Asia. And you don’t feed a billion and a half people, they start to get pretty cranky. They start overthrowing government and you have revolutions and things go bad. You’d say this was biblical in scale. But when they wrote the old Testament, there was only a hundred million people on the planet. But we have war in central Europe, which is largely, which is, from what I understand it, I think my information is pretty good, likely to drag on for some time.
Okay, this is not a siege of Kiev that’s going to go on for 48 hours, think months. Right now, the allied nations are funding Ukraine and Ukraine has a defense budget greater than Russia’s. Russia’s defense budget is 60 billion a year Ukraine’s defense budget is greater than that. So this goes on for a while. We have, I think the prospects of recession in Europe approach a 100%. I think the prospect of recession in the United States approaches a 100%. We have inflation that people are talking about inflation at 8%. I mean, I don’t get it. Your rents up 30%. Protein’s up 22%, energy prices are up 60% year over year. What else do people do with their money, other than food, energy and rent? So add those three numbers together and get 8.5%, only the United States government could do that.
So we have inflation and we have a very, very substantial correction in equity markets that’s probably about seven years overdue. And that’s going to, mostly what people focus on, I think it’s by far the least important thing. These recessions, we saw a recession in the tech market in 1989. That was a pretty good one. The dot com bubble, blow up about 2000. That was a pretty good correction. We had 9 11. I mean, you can remember 2000, 2001, 2002, 3000 software companies went out of business. NASDAQ went, I think, from 5,000 to 1200, as I recall, and the thousands of software companies went out of business. And here on highway 101 in Silicon Valley that you know very well, all the buildings were transparent. And so then we had 2008, which was a zinger, associated with subprime.
Now in each of those times, we had market excesses where things were crazy. Everybody knew it was crazy. Everybody knew it couldn’t last and they, then it blew up and everything got cleaned out. It kind of returned to normalcy. Now this economic expansion, which is, I believe the longest economic expansion in history, was sustained for probably five to seven years too long by this excessive monetary and fiscal policy in Europe and in the United States, these guys are printing, 1, 2, $3 trillion a day. The fed is printing, a hundred billion a month since 2008 in quantitative easing. And so that was basically welfare for the rich, that was inflating these equity prices. And so this carried on too long and now we’re going to see a correction. Candidly, I don’t think it started yet. I mean, it started, I think it’s got a long way to go. I think this could correct another, say it’s corrected by 20, 25%. I think it’ll get to another 30% before it’s over.
We’re seeing the first phase of what we see in these, is first the market volatility. Then you get to the hiring freezes. Then you get to the layoffs in the tech companies, which we’re seeing, whether it’s Salesforce or Uber or Twitter or Amazon, Tesla. Next, we’ll see all the companies that don’t have cash and are unable to generate cash, they’re unable to get funding in capital markets. So they go out of business. And so we’ll see, I guess a few 1000 software companies, technology companies, go out of business. I just hope it happens quickly. I think these are like natural forest fires. They’re natural phenomenon. They’re fundamentally healthy things. And it clears out kind of all the craziness, all the specs and all this business of everybody pretending to work from home in their pajamas and getting paid in Bitcoin. So all those days will be over and we’ll get back to work and it’ll all be good again.
Daniel Newman: All right. There’s the show everybody… No, no, but Tom, I mean, you hit on a lot of things and for the sake of this audience, some of those big, big macros that you talked about, I’m not running away from them, we’re not really a geopolitical show, but we talk about the tech industry and markets and these things impact the tech industry. So I definitely like all that crossover. And so let’s stay with that. I mean, I think also by-
Tom Siebel: I mean, really Daniel, the market might be up or down 2 or 3% today. Some days the Dow moves a 1000 points one way or the other, and it’s the end of the world. But I mean, really we’re looking at a billion to a billion and a half people who might not eat this year, get your mind around that. I mean.
Daniel Newman: And we don’t care. And I mean, this-
Tom Siebel: Nobody cares, everyone wants to talk about racial equity and all these things that are important. And I believe that they are important. Hey, and this is the year 2022, there are 30 million people enslaved on the planet earth this year. And everybody knows it. In the Middle East, in Asia, in China, with the Uyghurs and other, 30 million people in 2022 are enslaved. And when last time you heard somebody talk about that? Rips your heart.
Daniel Newman: We definitely seem to like to keep the narratives to things that support certain views. Let’s just put it that way. I’m going to play the safer role here. And I’m going to let you play the guest role. And you know what, Tom? I actually love that you’re bringing honesty to the discussion. Yesterday I was at an Amazon event in Las Vegas called re:MARS and it’s machine learning, automation, robotics, and space. But there was someone on stage talking about finding low earth orbit, finding a solution to getting people off this planet. Because effectively, no-one’s willing to have the conversation that we don’t know when we’re going to hit capacity, in terms of resources.
We like to talk about climate change and all this stuff. But no-one’s really talking about the practical event of, okay, when we get to 8 billion, is it 10 billion people that can live on this planet before we basically going to chew up more resources than we can create? Where are we going to live? And maybe going this space is a little big idea, and maybe that’s not the right… But an extinction event though, is a topic that no one wants to talk about, that this could actually happen. But we like to talk about it when it’s a kind of a soft feel thing, right? Like carbon footprint. But we don’t like to actually talk about it when it’s like, well, what is this really all adding up to?
So to your point, you’re bringing out the big bang here. The big bang is that there’s real big problems out there that are bigger than the problems we tend to spend a lot of our time focused on. And for instance, the volatility of the market from one day to the next, for most people that even have time to care about the market, it’s probably not enough that’s going to change whether they eat, whether they can put gas in their cars, whether they can put clothes on their backs, whether they can pay for a roof over their head. It’s like whether or not they can take some exotic vacation or fuel their jet. I mean, that’s the type of stuff that-
Tom Siebel: That doesn’t matter, but inflation matters. Because inflation is killing all the people who don’t own equity. So guys-
Daniel Newman: Let’s talk about that real quick. Let’s talk about-
Tom Siebel: We don’t have the luxury of owning Facebook stock. Okay. Or Amazon stock, or whatever the bid might be. And so here we have all the people, working people, who work in restaurants and hardware stores and construction sites, and these guys are being slaughtered. I mean rents are up 30% year over year. Fuels up, God knows what percent, it’s like $7 a gallon in California. You see it 5, 6, 7 bucks.
Daniel Newman: Better here in Texas,
Tom Siebel: Texas, guys probably give it away.
Daniel Newman: By the way, if people don’t think that oil is political, I was reading something somewhere that gas still, right now today in Kuwait, is like 20 cents a gallon.
Tom Siebel: Really?
Daniel Newman: Yeah, it’s not the same everywhere. There’s a lot of politics and tax in gas, but we don’t also spend a whole lot of time really informing people how that works. So gas isn’t five and eight and 10. And like in Europe, $15, what amounts to $15 a gallon everywhere, because there are parts of the world that have democratized gas and oil differently than we have here. But you know, this is like runaway politics, Tom. And by the way, fascinating stuff. And to your point, I think we can agree on one thing, 8% is not the real number. 8% is not even close to the real number of inflation right now. And with people’s assets being blown up. And by the way, the asset that’s about to get blown up that most people aren’t talking about, is in most parts of the United States and in other parts of the world, is going to be their homes. Which is the one thing that everybody’s had inflated for some time to give a lot of comfort on that home balance sheet that we keep talking about.
That number is going to come down because with interest rates popping, unless you live in a market that everybody wants to be in and has very little volatility in elasticity due to demand, supply’s going to go up, refinances have already gone into the floor. People aren’t refinancing anymore. Your buying power just went down with every 1% interest, your buying power goes down by hundreds of thousands, especially in markets like California. This market could come to a standstill. And we did it again though. The Big Short reference, we did a lot of the same stuff again. The only thing we did better this time around, is we’ve had low rates for so long Tom, that most people have gotten into fixed mortgages. So we don’t have that massive bubble of adjustables that are about to come due.
I do want to take 10 minutes and talk about AI though, a little bit, at scale, because you are a pioneer in this space, you’re doing something different. Can we just, I’m having a ton of fun. I could do the whole show just about what’s going on in the world. But I talked to someone that you had worked with in your career, just recently, Bill McDermott, check out the last show. And I spent some time with him, and him and I… So I did an op-ed on Market Watch. He’s been talking about this in public a lot, and he’s talking about this idea that a lot of these problems, these macro problems, that you, our supply chain being busted up, the healthcare crisis and how to figure out how to get food into the right parts of the world. And then of course, how to deal with our labor shortages, which is more of a entitled problem for big companies that want to get even bigger, but still are going to be solved with technology.
Talk a little bit about that because you know, with C3 and everything you’re doing, it seems like you’re trying to figure out how to help industries leverage data, to be more efficient. Is technology and AI going to be the modality to get us out of some of these problems that humans are clearly struggling to solve?
Tom Siebel: I think that really require kind of responsible government policies, responsible fiscal policies. And that’s what’s really going to take to fix this. Now will information technology contribute to making the world better? It has, and it will. And if we look at the last 40 years of information technology, it’s gone from order of $200 billion business to maybe, five or 6 trillion today. And we have this big step function of information technology that’s come online in the last decade associated with elastic cloud computing, big data, the internet of things and predictive analytics. And these, this step function of technology enables us to solve classes of problems that we haven’t been able to solve before. So in places like Oracle, where I was, Siebel Systems where Bill McDermott and I worked together. SAP, where Bill was a very, very important leader. We built this whole class of enterprise application software for ERP and CRM and supply chain management manufacturing. And that’s about a half a trillion dollar business today, annually.
And so we have trillions of dollars of these installed applications from SAP and Oracle and PeopleSoft and Siebel, JD Edwards and others, that allow us to run businesses and healthcare systems and governments. And they report kind of, they allow us to perfect kind of 2020 hindsight at what happened last quarter or last year, what was our revenue, what were our inventory levels? What was our customer churn? What were the breakages in our supply chain? Which one of our devices failed? Well now we have this area where AI intersects with these enterprise applications. And is basically, and what we refer to as enterprise AI, enables us to take these applications and make them predictive rather than retrospective.
And when we make these applications predictive, rather than reporting on which device, which transformers, which pacemaker, which jet aircraft in the United States air force failed in the last six months or 12 months? It’ll tell us prospectively, which of these devices are going to fail in the next 100 flight hours in the next 30 days. So we can replace the auxiliary power unit in the aircraft, but we can replace the transformer in Rome. So the aircraft doesn’t fail or the grid doesn’t fail. So rather than tell us how many customers left us, or what are customer churn rates at, name the company, whether it’s Bank of America or Verizon, these applications, when we make them predictive, will tell us now, okay, what customers are going to leave us in the next 120 days or 60 days? By name. So we can take appropriate action to find out why are they dissatisfied, make them satisfied and save the customer. Fraud detection is a big issue where, in financial institutions, we have requirements, very rigorous government requirements through report, for example, on adding money laundry, because a lot of bad actors do that.
And so we have this AML requirements where we have to report on what was the frequency and scope of AML activities, that name financial institution. And we have to report on that quarterly. And if we don’t do that correctly, see Deutsche Bank for details, CEO gets to rewrite his resume and you get another 10 billion in fines. So using, when we make these applications predictive, we can identify these fraudulent transactions in real time and avoid the fraud. So this is what happens, rather than reporting what inventory, where our supply chain broke. We can use predictive analytics to identify where our supply chain is going to break, okay. And mitigate, figure out how to get the parts to Moline so we can make the tractor.
So that’s what predictive analytics all about. This is what we do at C3 AI in enterprise AI. This promises to be a 600 billion addressable market in 2025. I believe we’re the world’s leading provider of this stuff, these kind of applications. And we do it for aerospace, oil and gas, utilities, manufacturing, banking, telecommunications, and health, and today and oh, defense and intelligence, also in a big way. And so what we do is we take the kind of applications that Bill used to make at SAP and we make them predictive. Or we make the CRM applications that he makes now, Bill being one of the great leaders in information technology and a friend and a former colleague, what he makes essentially is CRM and customer service applications at ServiceNow and makes them predictive in nature.
And so that’s what this adventure has been all about at C3 AI. We’ve been at this for about 13 years. We’ve invested about a billion dollars in the technology foundation and we’ve built… So we’ve built a platform and we’ve built 42 turnkey enterprise applications to meet the needs of the value chains of oil and gas, utilities, life sciences, what have you. It’s about a quarter of a billion dollar business. It’s growing at a 40% compound annual growth rate. So we’re one of the fastest growing software companies out there. We have a billion dollars cash in the bank. So we are an ongoing concern. And in your last quarter, I think we consumed, we burned about 15 million. So fast math, I think at this rate, we’ll run out of cash in 67 quarters. Don’t worry, we’re not going to run out of cash, but it’s, so in many ways, Daniel-
Daniel Newman: By then the market correction will be over, Tom, by the 67 quarter. 67 quarters from now, the market correction will be over.
Tom Siebel: Unless the government completely screws this up which is possible. The, I mean we are running a 80% gross margin business. So it’s not difficult when we’re running a 80% margin business, it’s not difficult to be profitable. And so it’s pretty easy. And so we have a clear path to attain that. And so the game that we’re playing, like we played in the early days of Oracle, when I was there. And like we played in at a company called Siebel Systems, that everyone called, that I started and we created this market that the world knows of today as CRM, is to establish and maintain a market leadership position in this space. Now, I’ve spent my entire career basically preparing for the next economic downturn. So in December of 2020, we raised about a billion dollars cash in the public markets. And we have about a billion dollars cash in the market today, plus or minus 50 million.
And so we are very, very well positioned to continue to grow, to continue to innovate, continue to prosper in this space. So we have, I think 825 people in the world today. We’re hiring in Paris, Rome, London, Singapore, Sydney, New York, Atlanta, Chicago, and here in Silicon Valley. We have a very unusual culture because we’re all back at work. So in this building with me today are 430 people. If you look at our parking lot, it’s the only parking lot that’s full in Silicon Valley and our offices are full today in all of those cities I mentioned. We’re back at work, working on very important mission and critical applications for our customers.
Daniel Newman: So, I want to pause you because there’s a lot there to unpack and you kind of answered three or four of my other questions, which is great. Kind of a monologue, but you hit a lot of points. One is, clearly your remote work theory is no. In most ways, like I said, maybe an odds and ends person in that you just think is unbelievably talented and not in a market, maybe for a while, but it sounds to me like you believe people need to be together or congregating. You also serve industries that think a lot that way. You’re talking about the banking industry, which said, “Get back to work.” Healthcare industry, there’s no way you can do that remotely. The oil and gas, those people are out on rigs and drilling and doing their work. They’re in the offices in Houston or in the Middle East.
So you’re kind of saying, we’re going to live by the same standards that we want the clients and the customers that we’re building technology for to live by. And I think this, by the way, we’ll come back, Tom. I, for instance, run a mostly remote company of analysts, but having said that, I think we’re going to go back in history and realize we got a lot of this wrong, about how we treated this and how we handled the continuum of hybrid to On Prem, to remote. And we didn’t learn enough during these last few years. So I think you’re onto something, but I think we’re going to, in the end, it’s going to be whether or not we ever look back at the data. It’s kind of like I make a great prediction for the market in 10 years, get a lot of attention for it. But the problem is no one’s going to ever go in 10 years and say, Dan, how did that prediction go? They just thought it was really interesting that I made it right now.
I want to talk to you about one other thing though. You’re trying to pioneer something. And I guess, this is probably the most granular I’m going to get about AI here, but I want to end with something that’s for my geekier part of my audience. The less markets, more geeky. A lot of people say AI can’t just be out the box. That’s not really, that’s not a thing. Everybody’s unique need is so custom and differentiated. You seem to really have the fundamental belief that whether it’s the way CRM was built or ERP was built, AI can be built kind of the same way. And it says, “Hey, you’re a bank? Here’s your software.” “Hey, you’re a oil and gas company? Here’s your software.” And of course there’s always in history, been modification, right? There’s always been consulting firms to customize your Siebel deployment, right back in your day. Is it ever going to get to that point? Because I still feel like you’re only, you can’t be more past than past the first inning, Tom, in terms of the size of the market that you’re trying to build here.
But when do we get there? When do people actually start saying AI out of the box is a thing in the enterprise space?
Tom Siebel: Well, it is a thing and I’ve proven it. So, what is, so we built something called a model driven architecture. Technology that we have all the patents on for enterprise AI. And whether I’m doing anti money laundering at a bank, stochastic optimization to supply chain in a manufacturing company, or analytics for upstream, downstream, midstream at Shell, hydrocarbon loss accounting, production optimization and Shell has say, manages, monitors like 13,000 devices with our platform today, across about a 100 different applications. And some of their assets are things like Pernis, Pernis is the largest refinery in Europe. They process half a billion barrels of oil a day. So that would be an asset about the size of 10 aircraft carriers.
Now, for all of those applications, which sound quite different in different industries, 95% of the code that I have running in those sites is exactly the same. All that varies are the data sources, the user experience expression and the machine learning models. The rest of the guts of this thing that handles the complexity of data fusion, queuing, ETL, encryption in motion, encryption in rest, access control, machine learning pipelines, what have you. That, it’s all the same code.
So we’ve demonstrated that 95% of the code that I have running, is the same across my entire customer base in all of these industries, be it defense or healthcare products. So I think that question is over and it is, that is the secret sauce at C3. This is why we succeeded at establishing ourselves as the largest player in the market.
Daniel Newman: And like I said, I think you’re emphatically, right. And I’ve worked with your organization, you have full transparency, as an analyst on advisory work. And that question wasn’t staged. That question was a legitimate question, but we also know that in the tech space, in what’s considered a high growth market, sometimes the market says, “Oh, only 40%? You should be growing at 4000%. And I don’t understand why that’s not happening and I’m not investing until I see you hit earnings growth or this…” And what I’m saying is, this goes back to the beginning when you said the market, maybe it does, maybe it doesn’t matter right now.
Tom Siebel: Let me comment on that. And so, and I’m not, there’s companies like Snowflake, great, great companies, okay. That are distributing, they might have 500 new customers in a quarter, that they’re selling, to whom they’re selling a $20,000 product. A large customer will have paid me a hundred million dollars. So we’re operating the European grid. We’re, for example, dealing with the distribution of a hundred billion dollars worth of food products at Cargill. We’re dealing with applications in the defense intelligence community, that if they don’t work, the United States air force can’t do its job. And so the issues that we’re working on Dan, is if our projects do not succeed, people die. And so this is not something you do from home in your pajamas. Okay. People die if we don’t do our jobs. And I mean really.
And so this is very serious stuff. And I can’t take on a 100 customers in a quarter. I can maybe take on 20. But they’re mission critical applications. And if we fail in what we do, the environmental consequences are deleterious. The eco health consequences are deleterious, people starve, the air force can’t do its job. So we take this very seriously. The other thing I would say about work from home, I think there are areas, like a research organization, or a law firm. I think those are jobs where that can be distributed working from home. With kind of these high end knowledge workers, who really can coordinate what they’re doing. Now, if however, let’s go to SpaceX. Okay, well we want to develop a rocket that goes up in outer space and then come back and lands itself, okay, let me help you out. We’re not going to do that with a 100 people on a Zoom call, from 4:00 to 5:00 on Tuesday.
I mean, you got to be working elbow to elbow on these advanced technologies, whether we’re dealing with when we’re inventing new things. And we’re inventing, very, very new technology here. And candidly, it takes very bright people, working elbow to elbow with the customer and we fail and we fail and we fail and we fail and we fail, until we succeed. And it’s so, kind of thinking, depends on the type of work.
Daniel Newman: Yeah. Well, I’d say you hit it on the head. It’s a continuum. I think you hit it on the head, that the market doesn’t fully understand what the complexity is. That you’re not just another offering off the shelf doing some software that maybe makes some small difference in a workload, or what I called features that became companies, which was a big trend throughout the last two years of beta growth. But that you are really, if you think about like large SIs and how they have to grow and the complexities of growth as an SI, but at the same time, a very sticky industry, which has been my biggest bull case. When I talk about how sticky the relationships that you’re creating with these companies are. There is no other option once they’re down the path with you, that exists today. Not to say someone won’t compete and come into market. But being early and having something so sticky has a lot of strength, Tom.
And I think we could keep going and you could come back at me. I keep going back at you. But you’re onto something. It’s an important space. And yes, where we started this whole conversation, the world is pretty messed up right now, but I do believe technology will be a key contributor to solving a lot of the problems that we as humans, without it, can’t seem to solve on our own. Tom Siebel, CEO, C3 AI. This was a lot of fun, very interesting as always. And of course all the best luck to you, your company and all the different things you’re doing outside of the organization these days.
Tom Siebel: Thank you, Dan. Great to see you. And I wish you all the best luck in Austin.
Daniel Newman: Thank you, sir. Talk to you soon.
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Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
