The AI Gold Rush: Should Companies Build or Buy AI Solutions?

AI is no longer a futuristic concept; it’s here, and companies are racing to integrate it. But with rapid advancements, many businesses are facing a tough choice: Should they build AI solutions in-house or buy them from external providers?

In this episode of the MVPF InnoSanity Podcast, host Baby Jessi Parker speaks with Jasper Wilmes, Venture Architect at MVP Factory, about the AI boom, the risks of adopting off-the-shelf AI, and how companies can strategically integrate AI without losing control over their data. If you’re trying to figure out how to unlock AI’s value while staying competitive, this episode is a must-listen.

Here's what they talked about:

Baby Jessi Parker: Welcome to InnoSanity, the podcast where we dive deep into the accelerating world of corporate innovation and venture building.

Today's episode is the first in our two-part series on monetizing data with Generative AI. We’re exploring one of the most exciting and transformative topics in tech—how AI, particularly Generative AI, is reshaping industries, fueling new business models, and presenting both challenges and opportunities for startups and enterprises alike.

Joining me today is Jasper Wilmes who will talk about the AI boom and venture building and the opportunities it brings, and how somebody, maybe yourself, a colleague, a friend, or even a family member, can leverage it. We’ll talk about some of the tools and concepts that can help achieve strategic business goals.

But I’ll let the expert talk about that.

Meet Jasper

Baby Jessi Parker: Jasper, welcome to the show. Before we dive into the topic, let’s have a short introduction about yourself. Who you are, what you do, and, I don’t know, maybe a hobby if you wanna throw something in there. But tell the people who you are.

Jasper Wilmes: Hi everyone. Jasper here. So I'm a venture builder at MVP Factory. Essentially, what I do is build ventures from scratch to investment and then hand them over to external founders. My role is to take a company’s strategic investment scope, turn that into a specific idea, validate whether that idea makes business sense, and then help founders secure their first round of investment. Once that’s done, I move on to the next venture.

Right now, I live as a bit of a nomad. I’m currently in Portugal, but I spend most of my time between Portugal, the Netherlands, and Germany, depending on the season and the weather.

Baby Jessi Parker: You’re getting all the sun right now. There’s none here in Germany at the moment. There was some yesterday. But anyways - so, yeah, AI. It’s nothing new, but at the same time, it’s new because you see it everywhere. Maybe it’s lost a bit of that “newness.” AI has been around for a long time. But then, in November 2022, ChatGPT hits the market and takes the world by storm.

With it came a whole revolution of things. So the question is, what is your take on the AI hype that's currently going on, specifically in the startup world?

Baby Jessi Parker: So, let’s jump into the topic. AI is everywhere - it’s new, but it’s also not new. AI has existed for a long time, but then in November 2022, ChatGPT launched, and everything changed. Suddenly, AI wasn’t just for tech companies, it was everywhere. What’s your take on the AI hype that’s happening right now, especially in the startup world?

Jasper Wilmes: It’s fascinating. Like you said, AI isn’t new, and neither is Generative AI. The first chatbot existed in the 1960s. But the key difference is accessibility.

Before ChatGPT, AI models existed, but they weren’t accessible to the public. Only big corporations could afford them. I remember giving a workshop on AI at EY a few years ago, and most people weren’t interested, it felt too far off.

Then, ChatGPT launched, and for the first time, anyone could use AI for free. That was the game-changer. Suddenly, AI wasn’t just a theoretical concept; it was a tool people could interact with. And because of that, the demand for AI skyrocketed overnight.

Baby Jessi Parker: That’s an important shift. And now we’re seeing companies scrambling to adopt AI. But with that comes a challenge - how do they do it in a way that makes sense for their business?

Jasper Wilmes: Exactly. This is where we see the buy vs. build dilemma.

The Buy vs. Build Dilemma

Baby Jessi Parker: Let’s break this down. Companies who want to integrate AI have two options: buy an AI solution from a startup or build it in-house.

Jasper Wilmes: Yes, and both options have their pros and cons.

If you buy AI from a startup, it’s faster and doesn’t require hiring AI engineers, which are expensive and scarce. Startups also move faster and can iterate on technology quicker than corporates can.

But there’s a huge risk: when corporates buy AI solutions from startups, they’re essentially feeding data into the startup’s models. Over time, the startup learns from the corporate’s data and improves its AI.

What happens next? The startup can take that AI and sell an even better version to your competitors. That’s what I call the Trojan horse problem.

Baby Jessi Parker: Wow, so companies could end up training a startup’s AI, which later gets used against them?

Jasper Wilmes: Exactly. That’s why some companies choose to build AI in-house. But that also comes with challenges - AI talent is expensive, development is slow, and by the time an internal AI tool is ready, the technology may already be outdated.

Klarna’s AI Playbook: A Corporate Success Story

Baby Jessi Parker: So, Klarna did it, and they did it very well. I don’t think this was their first try. I think they’ve tried things beforehand, but this is definitely a successful one.

You know, kind of shifting it then towards a company that is starting from zero, how could they tap into AI and leverage it for their business? Where do they start?

Jasper Wilmes: Yeah, so there's this very classical dilemma that corporates face when adopting AI solutions. But before we get into that, let me give you some actual data on how Klarna’s AI assistant has performed.

So Klarna rolled out their AI-powered customer service assistant in January 2024. After just one month, they had 2.3 million conversations, which accounted for two-thirds of all customer service chats. It performed the equivalent work of 700 full-time agents. The satisfaction rate was as high as if a human handled the conversation.

And here’s the most impressive part: the AI assistant was able to handle customer service requests in two minutes, compared to 11 minutes when handled by a human agent.

They estimate that, in just that single month, it improved Klarna’s profits by $40 million.

Baby Jessi Parker: That’s crazy. $40 million just from optimizing customer service efficiency?

Jasper Wilmes: Exactly. And this is just one example of how companies can leverage AI to increase efficiency. But that’s only part of the story. The real opportunity lies in how AI can be used to monetize corporate data and create entirely new revenue streams.

What’s Next? Leveraging AI in Venture Building

Baby Jessi Parker: So, AI is here to stay, but companies need a smart approach to adoption. If they buy, they risk giving away their competitive advantage. If they build, they risk falling behind on technology advancements.

In Part 2, we’ll go deeper into how venture building can help companies bridge this gap. We’ll explore how corporates can leverage AI for new revenue streams, the role of AI venture studios in helping companies move fast, and real-world examples of AI-driven corporate ventures.

Thanks for tuning in to Part 1 of this discussion. See you in the next episode!

Interested in a deeper dive into AI Venture Building? Have a look at our whitepaper - get your free copy here.