For most people, the mention of “data” conjures up certain ideas. Usually, it’s a mental image of pages of numbers, arranged like a mathematical equation. It could be scientific findings, patient records, or the history of anyone’s online browsing, all condensed into lines of code and keywords.

But the truth is that data is so much more than that. As humans, we leave data everywhere. It’s in the sticky notes left on the fridge, the turned-over pages of books, the scribbled-on napkins left at restaurant tables, or scrunched into the bottom of bags. There’s enough data out there to explain the human decision-making process in a way that even an alien could understand – that is, as long as we can bring it all together.

Now, that leads us straight to our problem. There are plenty of databases out there, although not nearly enough to hold and showcase all of the world’s data. That’s a lot of potential power at your fingertips… Maybe too much. No one can scan through that much information: it’s essentially the needle-in-a-haystack quandary.

But as I see it, that is where we face a tremendous opportunity. Collecting and utilizing all of the “human data” throughout EQT’s global platform is something that will help us build a long-term asset. Today, we collect, analyze, and synthesize what makes a decision, well, a decision. The system sits on top of a vast proprietary database containing hundreds of millions of data points about companies, people, and the connections between them. With thousands of businesses starting up every day around the globe, Motherbrain can track and assess many of them – a task too daunting for even the most experienced and willing-to-be-sleep-deprived humans.

I lead the data teams at EQT and yet, my past isn’t filled with coding and computer clubs. And that fits the mold with our firm’s confident and differentiated way of doing business. My background is in people and human-decision making, and that allows us to think about tech differently. As a result, and luckily for my vitamin D levels, my team isn’t stuck in the basement. Instead, the deal team and the engineers work side by side, using data to find the answers to the questions quicker than most humans could ever do alone. And that’s what makes Motherbrain so fascinating in my opinion. The platform doesn’t look like a binary record of dense statistics, unintelligible to anyone besides technical experts.

Instead, Motherbrain collects and displays the information in a way that humans actually understand. You can see external records of facts and figures, of course. On top of that, though, is a collection of all the thought that goes into a private equity investment – meeting notes, people in common, jotted-down numbers, lengthy powerpoints or not-so-lengthy emails. After all, it’s been built – in part – by people who prefer phone calls to Python notes.

Here at EQT and elsewhere, the system can help with deal management workflow, market analysis and monitoring (like analyzing target companies, peers, and competitors), and talent sourcing. Motherbrain lets anyone manage pipelines, add assessments, and track advisors. Looking even further ahead, it will become a system that uses AI to integrate and distribute knowledge, letting every single employee in the company access the expertise and deal knowledge that would historically live in everyone else’s heads.

Now, I don’t work in a team with the same background or thoughts as me – on the contrary, our differences are key to our collaboration. But see, EQT’s philosophy is built on experimentation, trial and error, and perseverance through difficult times. That’s our shared set of values, above all else. The company is as open-minded as it is ambitious, so no matter whether we ran into problems (and there were many) or stumbled upon a happy opportunity, our team grabbed the chance to troubleshoot and brainstorm. Essentially, EQT runs into the storm, rather than away from it.

Of course, all of that collaboration came with a learning curve. Our internal teams had to get used to the new technology, and we had to see how they used it to help iterate and build the platform. After all, the best tech in the world is useless if no one uses it. That said, resistance is normal when you’re entering a new paradigm of technology. There is momentum out there, though. Companies are clamoring to make a name for themselves in the AI sector. Plus, over the last two years, funds have been putting more money behind their data science teams.

Motherbrain today is well past the initial development stage. The platform is continuously “learning” and improving its algorithms. But as you may have gathered already, I don’t see a world where human intervention isn’t valued – or even, essential. Algorithms and machines won’t necessarily replace humans, but I do believe that humans with algorithms will outperform humans without algorithms.

I liken it to chess sometimes. World Chess Champion Garry Kasparov’s book “Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins” talked about advanced chess. In that form of play, humans play against each other while running a war-game software, which helps to predict the outcome of possible moves. During the games, amateurs using the software outcompeted the grand masters who had on average more than 10,000 hours of practice. See, the experts were too rooted in their own biases and beliefs to listen to the machines, while amateurs worked in collaboration, seeing systems as tools rather than rivals. Motherbrain is designed to be that system for private equity firms – and in my opinion, those who see such technology as the next computer rather than a competitor will reap the biggest rewards.

Still, we can’t get complacent. We need to decide how to improve before anyone asks it of us. We must look beyond what is currently desired. We need to invent before the current technology gets old. At the end of the day, just because we invented something in the past, it doesn’t mean it’ll be useful in the future. In other words, pack lightly because you will have to travel.