Crunchbase CEO Jager McConnell in Exclusive Interview: "AI is now necessary for all companies. It's not even a choice."

Crunchbase has relaunched as an AI-powered predictive intelligence solution, shifting its focus from historical data to live, predictive intelligence. Crunchbase can forecast trends, startup funding rounds and acquisitions with up to 95% accuracy, according to Forbes. Crunchbase’s AI analyzes billions of market signals, integrating data from various sources—including government filings, traffic data, and engagement signals from its 80 million active users. This transformation positions Crunchbase as a forward-looking, AI-driven market intelligence offering rather than just a static database.

At the helm of this transformation is Jager McConnell, Crunchbase's CEO and a visionary leader in the startup and investment space. At this pivotal moment, he sat down with us for an exclusive interview, sharing insights on AI, Crunchbase’s AI-driven evolution, the business intelligence market, his leadership style and his predictions on how AI will transform the venture capital landscape—and much more.

Jager is a seasoned technology executive and product strategist with over 25 years of experience driving growth and innovation at leading tech companies. As the first CEO of Crunchbase, he was tasked with spinning the company out and transforming it into a high-growth standalone business. Under his leadership, Crunchbase raised over $100 million in funding and scaled to nearly $100 million in annual revenue, serving a global user base of over 80 million.

Jager led the development of both B2C and B2B revenue streams by implementing a Product-Led Growth (PLG) strategy, helping establish Crunchbase as an essential platform for professionals and enterprises across industries.

Prior to Crunchbase, Jager spent 11 years at Salesforce.com, where he held several key leadership roles. Most notably, he served as Vice President of Product for Sales Cloud, Salesforce’s flagship product and revenue engine. During his tenure, he oversaw the core Salesforce Automation (SFA) product line and played a pivotal role in shaping the platform’s evolution. His earlier experience in technical sales and marketing contributed to his well-rounded perspective on product development and go-to-market strategy.

With a unique blend of startup agility and enterprise expertise, Jager brings deep operational knowledge and strategic insight to any growth-stage or established organization. He is a trusted advisor to CEOs and founders looking to scale with clarity, speed, and precision.

Justine Ilone Siporski: We are here at GITEX EUROPE in Berlin with Jager McConnell, CEO of Crunchbase, the predictive intelligence solution that is the go-to source for startup and VC funding insights and information. Jager, it's great to have you here. Let's start with the big picture. How has Crunchbase's mission evolved since you became CEO? And what vision is guiding the company into the AI-powered future?

Jager McConnell: So historically, Crunchbase was about historical data–the one place we could go to find out what has happened at a private company. That surely was what we were when we started and when we spun out as an independent company. Today, Crunchbase is focused on predicting what will happen next at a company, not just documenting what’s already happened. That's where AI comes in where there's so much data about companies. We're using all of that data, not just the millions of companies that we track, but the users’ data, 80 million users that are using Crunchbase, to figure out what's going to happen to a company, which companies are going to become unicorns, which are going to get acquired, which are going to get funding rather than what has happened in the past. That evolution has been made possible by advances in AI.

Justine Ilone Siporski: What inspired you to pursue AI as a core component of Crunchbase’s evolution? 

Jager McConnell: I think AI is now necessary for all companies. It's not even a choice. If you want to stay relevant, you must have AI be part of your product, and Crunchbase is  certainly no exception to that, and data companies in general. It used to be that you could just have a certain type of data—static, historical data—and you could sell that and that would be how you become a data company. Now you have to have something unique, something that differentiates your data so you must use AI to figure that out because there's no way to do it without AI. 

Justine Ilone Siporski: Can you walk us through how Crunchbase uses AI to predict startup success or funding activity? 

Jager McConnell: Sure. There are thousands of feature vectors, which are factors we analyze to determine whether a pattern suggests a company is about to receive funding. There are countless permutations of those patterns that reinforce our belief in such trends. Some examples would be, are there more investors looking at this company profile than there used to be? That means that if more investors are interested, it's more like they're going to raise funding. Another signal might be when a CEO updates their profile, which leads to an increase in investor flow.  A strong indicator could also be a rise in traffic to their website or more people searching for this company on Crunchbase. All those things and there's many many more, make it feel like there might be a funding round coming and we'll use that in our predictive algorithms. But the reality is there are so many different signals no human can figure it out and that's where AI comes in. 

Justine Ilone Siporski: With AI at the core, do you envision Crunchbase eventually transitioning from a research tool to an autonomous decision-making assistant for investors?

Jager McConnell:  I am not sure we're going to be that but I can easily imagine us powering that so there's so many different investors that use Crunchbase’s data today. I know that they're trying to figure out how to automate as much as they possibly can, so it's easy to imagine that they completely automate using Crunchbase data. We've talked internally about whether or not we should pursue that. At this time, we're not, but it is an interesting idea to consider—whether we should push it and start making investments ourselves. The challenge of course is that would change the sort of business we are. There are a lot of regulations that come with that, so as of now, I'd rather just power any VC who wants to be more modern, who's thinking about how to do investing based on predictions. 

Justine Ilone Siporski: How do you go against biases in your AI systems, especially when you are making predictions that influence investor behavior or founder visibility? 

Jager McConnell: That's a good question. Our systems are always going to try to do their best to figure out what drivers are making us believe a company is headed for a major change. I just gave you a few examples of drivers that could indicate that a company is about to raise funds or that they're going to get acquired. Those drivers are individual discrete things. When an investor buys from us, they're using our API. We don't just tell them, "these are the companies that are going to get funding." We say, "these are the companies we think that are going to get funding. Here's our percentage of certainty and then here are the drivers", giving them each individual driver in the API that we believe is the reason why the company is likely to receive funding. As a VC, you get all of this data from us and then you get to decide which ones to believe or not. We focus on providing transparent, factual signals. The website traffic is increasing. The investor traffic is increasing. They're being more active on socials. They're hiring more salespeople. Whatever it is, those are all factual things. Our prediction is an AI-informed estimate based on all that information that seems to be pretty accurate, but that's how we think about it. Let's give all of those drivers to the investor and let them decide which ones they want to discount or believe are biased, because we're  implementing machine learning to figure out what we think is right. 

Justine Ilone Siporski: What's your take on such a statement that there is a risk that AI-powered tools could reinforce existing inequalities in venture funding. For example, by favoring startups that already fit a certain profile. 

Jager McConnell: I don't know if that's true, but how I think about our predictions is we're not looking at things that drive bias. Maybe an example would be, if you're an AI startup, our algorithms will think you're more likely to raise funding right now because it's true. AI companies are going to get more funding right now, so that is part of the algorithm. We’re very intentional about avoiding unfair or harmful bias in our predictions. For instance, if there was a new trend, like whatever comes next after AI, it may take our algorithms a minute to figure out if that trending topic has a high probability of investment. But there are so many other feature vectors that we'll be looking at that would let us still make a good prediction. Basically, it's a culmination of many signals rather than just one or two. When you have that many, it's hard to have a real bias. This is a good thing, helping to potentially limit existing bias by leveraging AI for more data-driven objectivity.

Justine Ilone Siporski: How do you see Crunchbase’s AI differentiating the platform from competitors over the next five years?

Jager McConnell: That's pretty easy because no other company has access to the proprietary data we do. And I don't mean what's on the profile. I mean, so much of our algorithms are based on our usage data. No competitor out there has 80 million people using their platform. And that anonymized user engagement data is a huge factor in the algorithms so someone would have to get that from us to compete. So when we do, we look at other competitors of ours, they have some prediction scores, but they are not nearly as good as ours because they're trying to just base predictions on historical data, what's happened at the company. That is public knowledge. In Crunchbase’s case, we have data that no one has access to, so it's not public knowledge, which gives us a big differentiation on how we make predictions..

Justine Ilone Siporski: Do you see your AI models eventually being offered as a standalone product or API for VC’s, banks or governments? 

Jager McConnell: It already is. Someone can just buy the API for our predictions and not use anything else from Crunchbase. It's absolutely a standalone product today and that's how most of our bigger customers use us. They don't use the platform, the website, they use the APIs. We have very large hundred-billion-dollar funding financial institutions using our tech and insights. They're just consuming our APIs.

Justine Ilone Siporski: How is Crunchbase using AI internally in general beyond product in areas like sales, marketing, or customer service?

Jager McConnell: This is a big initiative internally—we’re rethinking every department through the lens of AI. And it's not just that I use chatGPT to write some text, it's how we’ve fundamentally changed how we do work so really across every department there are initiatives. Obviously in engineering, they're using Cursor to figure out how to write code faster so now you see 20, 30, 40% improvement. From an engineering perspective, you'll see even more than that as that technology gets better and better. On the product side, we're using tools like Figma, the AI and Replit to build prototypes and show user flows with actual code. This makes prototyping more efficient, so the programmers don't have to manually write out the PRD anymore. They can just show you what they want to build, even with the PRDs. There are so many tools in each of these categories. Marketing is another huge area. There are websites like Icon and others that help you build advertisements and automated webinars. On the sales side, there's a tool called Qualified that is basically handling all of our inbound leads. We've seen our MQLs, the meetings that we're making, go from a couple hundred to 600, just tripling the number of views we have, all just because of AI. So every department, every single one, has been influenced by AI. If we were to build a company today and we had no employees, what technology would we use to accelerate us? We have 160 employees and my question is: How can I accelerate those 160 employees to act like a thousand employees? That's really exciting for us. 

Justine Ilone Siporski: How has Crunchbase’s mission evolved under your leadership? 

Jager McConnell: It's been a long time. It's been nine years and it started with a simple mission: If you are trying to research a company, we have some foundational data for you. Today, our mission is about empowering people to see what’s coming—predicting private market movement and surfacing high-potential companies you need to connect with or know about. And it's very much about predicting the future, and how we serve and empower the next generation of investors, as well as the corporate development, like the partnerships, how we make these companies successful and really raise up the visibility of these companies that maybe otherwise would be overlooked. I think there's a big opportunity for us to help companies become discovered. If we can help those companies get discovered, get funding, we are helping innovation grow in the world. That's a good mission.

Justine Ilone Siporski: Crunchbase has shifted from content platform to predictive intelligence solution. Did you experience any challenges to make that happen? 

Jager McConnell: Sure. We talked about this for years. We could do this, but the technology wasn't there. Now, AI has reached a point where we can do what we imagined doing. That was always a challenge. We had a higher new skill-set, but we didn't have data scientists. We didn't have data engineers who knew how to build this stuff so bringing that skill set and having us think differently, I think is part of it. And now there’s another challenge: How do we change our brand? How do we change how people perceive us as something new? Because everyone still thinks of us as, ‘Oh, I go there to look up funding information.’ How do we change that to ‘I go there to find out what's going to happen next.’ That brand change is still a challenge that we're wrestling with today, but I think it will change over time. 

Justine Ilone Siporski: How do you prioritize new features in such a fast moving tech landscape?

Jager McConnell: It's a few things. First, we had to push into this predictive space. Now that we have it, we have a lot of customers. We have tens and tens of thousands of customers that pay us, we're listening to them. Do they want this thing? What would they change about this thing? What can we do better? So, of course, it's always about listening to customers and then reacting as quickly as possible. As we launched all these predictive insights about companies about four months ago, now it's about: How do we iterate quickly. How do we improve it? What are we hearing from our customers? And are there extensions beyond it? For instance, yes, we can predict which companies are going to get funding now or which companies are going to get acquired now. The next step on that is, let's figure out: Who will make the investment. What should investors pay attention to? What company will acquire this company? From there, we can look even further out—predicting not just company-level events, but which investors might get involved, or which acquirer is most likely, and explore how public market trends may influence private company trajectories. All of these are things that our largest customers are asking for and that's why we push into that direction.

Justine Ilone Siporski: How would you describe your leadership style? How has it evolved since becoming CEO of Crunchbase? 

Jager McConnell: I am a very transparent CEO. I believe that there's no reason to keep any secrets from your employees. It's best to share everything. When there’s a challenge that we're having, everyone's aware of the challenge. And if some employees don't want to be here because they see a challenge, that's fine. I'd rather bring in new employees who are aware of the challenge and want to join the company because of that challenge. Radical transparency, radical candor. For instance, I'll go through all the board slides with all my employees the day after the board meeting. If I have an executive offsite, I tell all the employees exactly what we talked about so that they can hear my thinking and what's going on. All those things are part of my style. I also like empowering employees to make their own decisions so I don't micromanage, it’s just not my thing. I don't think innovation comes from micromanagement. Innovation comes from people solving their own problems, because they know that I trust them, and bringing me in when they really need to. 

Justine Ilone Siporski: What's the most important leadership lesson you've learned while steering companies to an AI driven transformation?

Jager McConnell: You don't have all the best ideas as a leader. So you have to create an opportunity for people to share their ideas. If I'm a scary person, if no one wants to talk to me because they're afraid of me or my leadership team, none of those good ideas come up—so I must be approachable. As a leader, you need to be willing and able to develop a good relationship with your employees so that they can come up with ideas and share them. That's my best learning of this time, especially when there's so much change going on. Every day there's a new thing. The only way we can do this, we collectively try to figure it out together.

Justine Ilone Siporski:  How did you guide your team through the journey of AI transformation? Was it challenging to bring everyone on board?

Jager McConnell:  It was January 2023, I did a huge presentation for the entire company where I painted this vision of what I thought Crunchbase could be and it was a demonstration of what we could be. And it was that, I think, that shifted the mindset of everybody. At least it started that shift. As a leader, you need to bring that vision and not just use words to describe the vision, but in my case, I had to show them the vision of the future. Once that happened, a year later, we had it. I believe that's an important thing for CEOs to think about: if you've got an idea in your head, no amount of words can fully capture it, sometimes, seeing it makes all the difference. That's where AI tools, like Replit and others, can help you build that vision more easily than it was in the past. 

Justine Ilone Siporski: How did you navigate resistance or fear among employees? Did you encounter any pushback, particularly regarding AI adoption or the company’s strategic shift?

Jager McConnell: I think there's always reluctance to change. In our case, on the product side it was: Is this even going to work? What if the predictions are bad? What would we do, if we spent a year working on this and then we realized the predictions aren't good? How do we take small steps quickly to validate? That's something that we talked a lot about. Now, I think this is more relevant than ever. Employees are afraid: Is my job at risk because AI is here? Am I going to get replaced with AI? A lot of people talk like that. I don't think that's true. I think people's jobs are absolutely going to change. You can't just hope you're going to keep doing the same job as always. Our world changed just like when the internet came along. People started emailing instead of writing letters. The world has changed and everyone eventually changed. That's true here in your job. So yes, maybe you were a support representative before or maybe you were a marketing person before and you were writing the tickets, or you were writing the copy. Now, AI is going to do that for you. That's fine. Now you can do 10 times more. Now you can have these agents working for you as your virtual employees. That's the new world we're in. It doesn't mean you get fired, it just means your job is different. But you're going to be able to do 10 times more and hopefully be 10 times more fulfilled by doing your work 10 times better, but we'll find out.

Justine Ilone Siporski: Now something more general. What was the hardest decision you've had to make as a CEO? And how did you communicate? Was it difficult? 

Jager McConnell: Transparently, we did a layoff in the middle of 2023 and that was a very hard time. In my opinion, any CEO who claims the hardest part of their job isn’t letting people go is not telling the truth. It’s always the hardest part of this job. In our case, these were good employees that we had to let go but as a startup CEO, you have a finite amount of resources. Crunchbase isn’t a big company with infinite dollars. So we need to figure out how to prioritize the business. And if we don't do that, the business will dissolve and everyone is going to be unemployed. So you have to make these really hard trade-offs. For me personally, that decisionwe was very difficult, but it was necessary at that time. But back to being transparent, we informed people a month ahead of time that we’d be giving notice—but it’s still a painful, decision for everyone involved.

Justine Ilone Siporski: What advice would you give to emerging leaders trying to build companies at the intersection of AI and data.

Jager McConnell:  I think it's just true for everyone right now: You can do so much more with less right now so there's no reason to raise a lot of money. There are always exceptions, but generally speaking, you can probably build a bigger company with less now so the challenge for anyone who's starting is: how lean can you build while still scaling impact? You hear these stories about one or three or ten employees getting to ten or fifty or a hundred million a year, that's the future. What’s your revenue per employee? That’s becoming the new metric of success. It used to be like a couple hundred thousand dollars was good. Now it's three million dollars and it’s good. So if you're a new startup, as a founder you should be spending half your time figuring out which tools can help you run your business in an automated way without hiring people. You don't need to hire as many, especially at an early stage. There's so much you could do in a weekend that would normally have taken you a year just a few years ago. 

Justine Ilone Siporski: Do you foresee a future where Crunchbase can predict not only startup success but micro-level ecosystem shifts like industry contractions or innovation hotspots?

Jager McConnell: So we already can, we just haven't put it on our website. If you see one company is going to fundraise in an industry, we can anticipate others will follow. We can track whether fundraising is increasing or decreasing compared to previous months or years, whether these companies are getting acquired, and whether market consolidation is accelerating. We can predict all of that very easily. Crunchbase is already able to forecast industry-wide movements, providing indexes for these industries or predictions at the industry level. 

Justine Ilone Siporski: What's one piece of advice you would give startup founders that most of them overlook? 

Jager McConnell: It's very contrary to what you would expect the CEO of Crunchbase to say, but "Don't raise money". Everyone thinks success equals raising money. Even on this screen right here. It's talking about how they've raised money. I don't think that's relevant anymore. If it's necessary, okay, but raise as little as possible. Don't celebrate fundraisers. You just diluted the company. Celebrate not fundraising. Celebrate not having to hire more employees because you were able to grow without it. That's the advice I'd give any founder today.

Justine Ilone Siporski: The last question. How do you see AI transforming the venture capital landscape in the next five years?

Jager McConnell: There's going to be more automation, of course. More robot investing and all those things are going to happen. I think retail investors are going to flow in a little bit more easily. So retail investors can invest in startups in a way they might have not done so in the past. At events like this you might have retail investors walking around and saying: I want to invest in this company or that company. I believe there will be mechanisms emerging that will reshape the VC landscape, making it more niche and specialized so the big checks continue to come from the VCs, but the smaller checks might increasingly come from everyone else.

Justine Ilone Siporski: Thank you so much for the conversation.