E693 | Alex Dang, The Venture Mindset: How Corporates Can Beat VCs in the AI Race – The Venture Mindset in Action

0:00Welcome back everyone to another episode of the UBCD podcast. Today we're diving into how corporates might just be able to beat VCs in the AI race, or maybe more importantly, how we can collaborate. Our guest today is Alex Danco, author of the bestselling book, The Venture Mindset, How to Make a Smarter Bet and Achieve Extraordinary Growth. Alex is a seasoned tech executive and innovation advisor with over two decades of experience. He was a product leader at Amazon, where he launched new businesses across e-commerce, supply chain, and AI, a partner at McKinsey, helping Fortune 500 companies build digital ventures, and today advises corporate leaders and investors on AI strategies, venture building, and applying VC principles to large organizations.

0:53This show is not investment advice, and the hosts of this episode may be invested in the funds and companies featured. We have an American on the show. So for that reason, I'm trying to speak as fast as the US ecosystem tends to do when they are in podcasts. Now I'll dial down the timer a bit. Jep, please tell everyone, why should we bring on Alex Dang to the podcast? Yeah, you brought the Scandinavian in, right? To slow it all down, right? For me, this is one of the ones that I've been looking so much forward to because I've had a dialogue with Alex for a long time. The book, The Venture Mindset, is one that I use myself and have used when I have done consultancy with large corporates because there's so many learnings that have been shared in this book.

1:36So for me, Alex is one of my heroes in corporate venturing. So really, really looking forward to Alex sharing what is the venture mindset and what is his belief, especially around AI. Andreas Yepper, thank you so much for having me here. Yeah, we're super thankful to have you on. We're obviously quite the voice in the corporate venture space. So before we dive into the AI conversation, let's just talk about the venture mindset a little bit. Obviously, your key piece that everyone out there will know you for, but let's just make sure that anyone that hasn't yet heard about it will hear about it now.

2:10Orton, thank you, Andres. And the venture mindset is a bestselling book, as you mentioned, translated into numerous languages at this point. It's a result of a 20-year research from Stanford of venture capitalists and all of their, some of them became unicorns. And that breadth of analysis and research translated into very specific insights. For instance, that majority of the wins of venture capitalists are focused on the asymmetry of the results or outliers which are generating 10x, 100x return. And that asymmetry is a very unpredictable world, meaning that majority of the companies which we know today, seven out of top 10 most valuable companies are or were at some point VC back.

2:54So there is something unique about how VCs make decisions. And that's what we wanted to study with Elias Treble from Stanford. And we identified nine principles, formulated them. And more importantly, we believe that these principles are critical for the world where uncertainty is high. So in a traditional environment, you can still rely on your traditional MBA classes. But whenever you meet with anything more unknown, say AI today isn't a no, we don't know what kind of a technology will win, then you should and have to apply venture mindset. It will just be more helpful and more efficient as a set of management tools.

3:34So you did this book together with Ilya, right? With all sharing all your findings and so forth. So after the release, are there something that came to mind that is not in the book that you have wished was in there? Yes. Yeah, but I think the key learning, because we launched the book last year, May 2024. Since then, the AI boom started to be more than real. Actually, my major discussion with all of my current clients is about AI is not the future. It's already here. The shopping behavior is already changing. So I wish I could just highlight the importance of the pace in our book, that the speed matters even more than ever before.

4:20So we highlighted the principles of that we used at Amazon when I was there, two beats a team, fast-paced approach, launch fast, MVP or MLP, minimum lovable product. But now what used to be take 90 days or 111 days to launch, and I always bragged about that timeline. Wow, we could launch a phenomenal app in 111 days. Now it's all about days, not like weeks or months. So I think the time has compressed and I would apply the 10x rule to pretty much anything that you've already read in the book. Say even the team. Do you need a two pizza team? Not anymore. So many initiatives could be launched with, I now jokingly call it one slice team.

5:05So meaning that one person could actually launch a startup or launch a feature or launch a product. I did that and I demonstrated that in my workshops that you can launch so many things alone with current AI tools supported by digital workers. So I think that's the major thing and topic that I would highlight. Maybe you can just try and translate for our corporate audience exactly. how the venture mindset applies to AI, because we went from this 10x, 100x mindset of having a portfolio approach. And yes, we all get that. And yes, we also get the importance of moving fast. But when it comes to AI, how exactly does that translate?

5:48Like I said, Andres, it's all about the scale and the portfolio approach that you mentioned. That's the important first step that any large organization, they have phenomenal amount of data, customers, they have access to supply chain, they have access to the distribution network. What they need is, to some extent, a mindset and bold moves to start experimenting and to start playing in the new field. And AI is not an exception. I think actually it will just let you launch way more initiatives. I refer to this as an innovation machine. So today, AI allows you to automate to some extent the innovation machine.

6:25So think of a very simple nano banana example. You might have tested if you ran a, b tests or experimented with some images as you were trying to promote the product. Now you can generate 100x, 1000x of a similar experience that's very personalized so that the personalized example or personalized offer to undress would be different and then the one to me, then the one to Jeff. Yep. I think that's where AI gives you this 100x lever. So the principle is the same. Launch as many small, bold bets with an outlier in mind so that the one that would generate 10x and 100x return, kill them fast. And I think that's another key skill, which so many organizations are missing.

7:13Do not scale the org before you get customer feedback. So keep it very small, similarly to startups, and then double down on the winners. In the AI world, exactly the same approach, but faster with a smaller team. Let me just try and split two things here. On the one hand, we have AI adoption, which is its own space and field. And then you can argue that you have the other side, which is CVC, corporate venture capital, which you are also very famous for. And you really understand those two sides. And I think it's important just when we talk about it here, say, are we talking about one thing or the other?

7:52Because CVC is investing in companies to then build a road, an inroad into innovation and venture and tech through that, which is not what we're talking about just before when we're talking about using AI to really innovate quickly. And maybe you can split those two and tell people how you think about it and where you see, do you think that AI as an investment field is relevant for every single corporate out there? Or no, no, no, that's for a special type. Majority AI, think of it as just how you can improve your business, ways of doing business, improve your products, improve your internal innovation machine, but don't necessarily go and invest in a ton of AI.

8:33Can you try and split those two? Because it's two different things. Andres, I would say that even the way that you framed the question, I think I hear the similar kind of a question regularly from clients. They're kind of adding AI to anything. I mean, what do we do with AI? And I think that's the wrong approach by itself, because that's a very technology backwards approach, which unfortunately in a corporate setting typically leads to, I would call it AI theater or innovation theater, where you see lots of cool stuff in press releases, but the moment when you actually touch the product, when you try to use the product, well, your chatbot starts to get stupid.

9:12And you know, I mean, we all experience that, right? When we try to give a call to call center, I don't know about you guys, but I always insist on talking to a human. Why? Because we still cannot fully, completely rely on so many AI tools and we would have cut through that noise. So the problem here is that great products and great businesses and great innovation is built customer backwards. Think of one click on Amazon experience. There is nothing truly innovative about that, though it was patented. But one click is a simple simplification of your life. Then you have a dash button, which you can press and instantly receive a product.

9:52Then you have Alexa that you can place in order via voice command. Now you have agents, shopping agents, which can do this on your behalf. So as you could see, the pain point is the same. The technology varies. So when you refer to CVC or internal innovation or partnerships or acquisitions, I would refer to that as tools to introduce new technology, new ideas to your customers, to your clients. So all of the above would work. So actually the best in class companies like Amazon or Alphabet, they do all of the above. They invest in robotics themselves. They acquire numerous startups, including many startups in Europe.

10:34They also have their own CVC-like fund, the Industrial Innovation Fund, which is investing in supply chain innovation and robotics. So I think that's the best way to think about for a top senior leader in a corporate setting. Use all the tools to improve and to reinvent on behalf of a customer, not for the sake of AI itself. Though AI may add you, Heather, on the Wall Street Journal or Financial Times, but I think it will last only for one day. So it's way, way better to keep a bigger picture in mind. From a European perspective, we are insanely good at regulation on this continent. So when I talk to corporates out there, I oftentimes see the AI department being closely connected to the operational side of a corporate and not used aggressively in lending new customer and new revenue.

11:33Where would you start with your AI activities if you were a European corporate? I think you touched a very important point. It feels because I work with companies globally, and whenever I talk to European CEOs and leadership, I feel that Europe overemphasizes consensus and to some extent downside protection idea, which is, to be honest, the opposite of what you should do when you face such a revolutionary change. technology, which may have an impact of internet or mobile experience. And I think that's a very important thing to keep in mind. It's not just another tool. That's not just a minor shift.

12:15It may have an impact of an internet. And imagine you are a bookseller or any brick and mortar retailer before e-commerce truly started. Can you outsource that? No. Can you just ignore that? Not really. So that strategy would not work. So we have to go, I would say, all in. And you're referring to that as making bold, big bets, aggressively expand and introduce this to customers. There is a challenge, though. There is a caveat that I would make. As a very new technology for an established organization, there are risks associated with any launch. That's why at Amazon, we use MLP as an acronym, Minimum Lovable Product versus MVP.

13:02I mean, it sounds like a funny tweak, but it's actually demonstrating that we protect the trust of a user. So launching AI, I would start with back office functions first, just to protect and to learn and to build that capability. So supply chain, you mentioned one, is not a bad idea because that's where you are kind of protecting customers from a truly bad experience. but not doing anything with the user, I think it's just leaving money on the table. And you could build a way better recommendation engine these days. You can improve your marketing activity. Why would you torpedo everyone with the same email versus actually tailoring that to the different users, even to the user of one?

13:43So I think that's important to experiment at scale across all the functions. But you start with the simpler, more understandable use cases first, and then you sit towards more customer-facing ones. I think it's interesting, right? Because we tend also in Europe to really look at AI as something scary. I sit in multiple boards, right? And I really see the challenge when you have somebody at the age of 30 and somebody at the age of 60 sitting in the same board, right? Because they use AI differently. the younger generation have a tendency to try out things. For me, one of the things that if we go back to one of the things in CVC, right, the average lifetime of a CVC is 3.7 years.

14:36I'd love to say it, right? And that's what we're trying to cure, right? But the European leaders, they tend not to know that much about corporate venturing and alias the venture mindset, right? So where do you stand on this? What would you recommend? I think I would start with what you identified as a generational problem. I would even call it that higher you are in the hierarchy, the less you start to use all the down-to-earth tools. And I think you should. The best way to truly experience AI and understand what's happening there is to try all of these tools yourself in a guided way, in a non-guided way, but still experience that.

15:17Because it will lead to two different outcomes. So you will understand the magic of how so many things could be done from your PowerPoint deck automation to put them together, a cool email to automating your workflow. I did that with the N8N tool, but there are so many Zapiers and others. You just do this, spend two hours, and you will learn way more than from many BCG McKinsey decks as a CEO, just because you will see what is possible. The number two lesson from that will be you will see the limitation of the system. Like we all use, I guess, chat GPT. I mean, because I would assume more than daily, I think 100 times a day.

15:59And then you see, well, I mean, it's not ideal. Whenever you type something, you receive a result and then you start to edit it. You start to tweak it. You feel, you see that it hallucinates. You see that, okay, 90 % tried, but 10 % troll. Sometimes 10 % troll is just enough to break the entire post or the entire message or the entire email. So I think experiencing both the limitations as well as the advantages of AI, I think that's what's needed. So my step number one, give to all of your senior executives tools to practice and to play with. I spent eight hours with the entire team going through different tools, explained RAG in simple terms, fine-tuning in simple terms so that people would feel the difference and understand the difference.

16:45I think that's the important first step. If it just works for one thing there, I think Marc Andreessen put it really beautifully in a podcast a couple of weeks ago where he said, people need to really understand that we all now in our pockets have access to the best intelligence out there. that who's Trump asking when he's like, he cannot access a better AI than you have in your pocket. Like we're all using the same. And the fact that like the democratization that that brings us all, inability is quite outstanding, I think, because it used not to be like that. That's true. And I would just refer to the principle of double down or quit.

17:28We do not know which technology would survive. We do not know which use case will be the killer use case. So we feel that there is some magic and the power of the technology. And I think everyone understand that. Just don't be fearful about that. I think the best way to fight this fear is to test that and see what works. And if it works, then you double down. If it doesn't, you just quit. So you keep the experience small. I think the worst, to be honest, the worst case scenario is that the CEO will make one day a decision. I want to go all in on AI, make a one single bet, bet the farm on that initiative.

18:03and then it fails. I think that's the worst outcome because you will just waste resources. Alex, that's the perfect segue for me to ask my question here, because I wanted to ask you, now we've spoken a bunch about AI in the corporate setting. So let's bring it home to the venture space, to the startup space. This is a podcast where primarily our audience are VCs, startup founders, and corporates that are engaging with the venture space. So tell me, where should a corporate fit in the starter space, the venture space when it comes to AI? Look, I think I prefer to start from strengths. We all know that corporates are slow, sometimes a bit more bureaucratic than needed.

18:42But the strength of corporates is their access to data, customers, supply chain. So use that as your advantage. More importantly, a small win across the portfolio scaled at the enterprise level will generate 100, 1000x return. So you can start small in one zip code or one country or one region, but if it works, then you scale it across the org, wow, and you have the 10x, 100x impact. This is not the case for startups, by the way. This is just the case for enterprise level. Do you advise starting that innovation initiative in-house by developing yourself or when do you advise, no, you should probably look for startups to partner with on this?

19:28And do you put it with your CVC to do these types of things or do you ask them to now scout different AI solutions that might be a fit for the company and say, yeah, we used to have you do this stuff in investing. Now, the more important thing is you actually bring meat home for us to help us really understand AI? Yeah, it's a very good question, but I will have to respond to that in two different buckets because if you're big enough as an organization to establish and have presence in Silicon Valley and to build the CVC network and get connected to startups, do that because that will give you lots of information and insights.

20:07It will also give you a phenomenal access that will outperform and out-innovate your direct competitors. More importantly, you will reinvent yourself faster this way. That's a clear learning from many technology companies. If you ask me whether you want to invest in startups and bring startups to build things or improve some of your procurement function or sales automation or do it yourself, I would say that AI will be such an important capability that you have to build an internal muscle to complement, at least to complement any startup that you bring in. Today, if you visit Silicon Valley, you will see so many smaller startups, which are AI wrappers around strong LLM models.

20:50I, to be honest, do not see the reason why not to build a similar thing in-house. Because their experience of that team might be actually weaker than your own internal understanding and knowledge. And that's your huge advantage as an enterprise leader. So you can build, by bringing the right talent in-house, you can build so many tools internal, like procurement tool to improve your account receivables or just review the invoices and matching them with contracts and collecting the missed fees or missed discounts or sales automation. Who would better know your sales process than yourself? So with the right talent, with the right mindset, with the right intent, with the right decision-making setup, I think you'd rather do this in-house by bringing some startups from time to time in case of the unique use case or already well-established use case.

21:45What you're describing here is, of course, the make wave, so to say, that many have prophesied or at least considered that we are going to see in corporate that. Why would you have millions and millions go out to SaaS products that are not in any way custom built for you when you can actually just whip them up yourself internally? Can you talk a bit about like in those explicit terms, do you think that that's overhyped based on your understanding of where corporates are and what's actually doable? Like where do you weigh in on that? That's a very practical question. If you have capability to build the product or the solution in-house, I would just go that way just because it will always be your endage.

22:32I always think about Amazon. Amazon really relied on external products and solutions because at the scale of Amazon and at the need of Amazon, we were reinventing things on the go. So relying on external tools was not the best idea. But not everyone is Amazon. Just to remind ourselves that, yes, sometimes we are lacking talent. But I just feel and fear that companies at scale of Nestlé, Bosch, Siemens, etc., etc., etc., they do have enough scale and capacity to invest in such talent. And they have to do that. They can compete and out-innovate even corporations like Google and Amazon and Microsoft because they understand nuanced details of their operations.

23:20They are building machinery today. They have all that IoT fleet already. So I think they have this natural advantage. It's literally about the ambition and making bold bets, numerous bold bets. And I think you will succeed. I think there's something, Alex, and I think you also talk about it a little bit in your book, right? There's something about what risks do you take on yourself as a leader, right? And here do not mean, you know, the CEO or so forth, right? We have a tendency to protect ourselves by using existing products, right? It could be using Microsoft and then Copilot that is within because that is then the tool that is supported, right?

24:05And that's a safe haven. how would you address that? Because especially, you know, not even the European angle, I think that also accounts for the US, right? When you work in big corporate, you have to be careful about what decisions you do take. Totally. And I'm glad that you referred to the book, The Venture Mindset, where we dedicated the entire chapter to incentives. And incentives drive behavior. So the way that you design incentives in your organization, your team will dramatically change what kind of decisions people will make. AI or not AI doesn't really matter. What you refer to is a very rational behavior.

24:49So think of an executive in any European city of a large organization, and then you're tasked to explore some high-risk paths. Would you truly take that risk? because the outcome could be that you fail. And more importantly, we know, and you guys are very familiar with VC industry, you fail 60%, 70%, 80 % of times. If you think about a V's venture capital, they will write half up to 70%, 80 % of all the investments. If you will just apply the same failure rate to any executive, most likely that cost will be fired. the best case, he or she will be sidelined and will never be asked to touch that stack again.

25:36And that's a problem because if you are such an executive understanding these rules, then you would never take, I would not even call extreme risk, any risks. So you would try to be in this mediocre kind of a range. So that's a problem. The way that you will solve that structurally, You have to change the incentives and say Amazon paid a significant portion of that compensation was in stocks rather than a fixed amount. And we're stimulated to take risks and make bold bets. You would not be a strong leader unless you think big. Google created separate companies like Waymo. Waymo would never be able to become a common thing today here in Silicon Valley.

26:20where you're now in the street, you can see numerous Waymo driverless cars without setting up the right way, the incentives for this company. So yes, incentives do drive behavior in terms of the compensation incentives, but also culture. I think that's another big, important element to that. I would just share with your audience that in my office at Amazon, I had press releases of products which I launched or my team launched. and some of them were successes, but some of them, actually more than half of them, were failures and I still kept them on the wall because that's demonstration that it's fine to fail and still I'm alive, I'm working more importantly and kind of promoted with a higher scope of products and projects.

27:07I think that's also important, the cultural aspect of it. Alex, I'd love to ask you a question because I've had quite a few serial founders on the podcast recently who are now coming around for their second run doing a startup but building natively with AI and what they're all saying is that they're building with smaller more senior teams and they are typically much more tech savvy each team member because everyone in their team are now almost product builders. Because as we described before, you can build an AI for almost anything, but then that means that anyone has to be able to build. Marketing is no longer weaving together service providers, knowing where to buy ads and knowing how to measure their success.

28:00It's actually building a product that can do all of that for you. And you just run that machine. I'd love to ask you, how are you seeing corporates navigate this? Because as a young startup that starts afresh, well, they'll just hire people with that talent. And then you just have a completely new modus operandi in the company. But what do you do with a marketing department? I used to run a small one with 20 people. But, oh, my God, that team would not have been able to run much less, build any AI machine. And Andres, first of all, all of your guests who are launching their second or third ventures, I think they have way higher chances of success based on statistics.

28:41So I wish them luck, but at the same time, I think they have really high chances to succeed and to become unicorns. And the majority of them, luckily, we're having more and more of those in Europe, are former unicorn founders. So it is incredibly important what's happening right now. I may want to join your venture capital fund at the moment when you start one, because that's such an access to zero entrepreneurs. I think it's a phenomenal advantage.