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Meet the man building the world’s first AI recruitment agency

With Artificial Intelligence poised to revolutionise business, Eureka speaks to Jim Stolze, tech entrepreneur, ambassador and founder of Aigency – the first agency to specialise in connecting businesses with AI algorithms.
jim stolze first AI recruitment agency

April 13, 2018

There has never been greater excitement about the potential for machines to automate work processes and revolutionise businesses. According to global research firm Accenture, artificial intelligence (AI) will increase labour productivity by 40 percent and boost corporate profitability by 38 percent by 2035. But these gains will only be realised if algorithms can successfully be applied in the business world. In short, somebody needs to put AI to work.

In 2013, tech entrepreneur and ambassador Jim Stolze got sick of discussing the potential of AI and decided he wanted to get his hands dirty. He founded Aigency, a recruitment company that connects businesses with the algorithms they need to streamline and automate their operations.

“AI has been a breakthrough in the making for 60 years. That is how young or old this science is, depending on how you look at it,” Stolze says. “The theoretical concepts are older than Alan Turing and a lot of the algorithms that we’re now using were actually developed in the 80s. That’s when scientists first created the core algorithms, but back then there wasn’t enough computing power to really make use of them.”

The other big advancement has been the availability of data. Back in the 80s, acquiring data involved going to a physical place and asking for permission to copy it. Now, APIs have opened up an enormous wealth of data sets that can be used train learning systems.

The combination of cheap computing power and abundance of data has prompted enormous investment in AI research. Global professional services firm Deloitte predicts that AI deployments will double in 2018 compared to 2017, and then double again by 2020. With exponential growth expected in the sector, more and more firms are reassessing their entire business model to incorporate the technology.

“Everybody wants to be in this sector now, but when I first started Aigency things were still in their early stage. I could see all of this potential and I couldn’t help but start to question what it meant for business, and what it means for society,” says Stolze. “I decided to quit everything that I did. I fired my clients, I left my work as ambassador for here in Europe, and I began figuring out how to match algorithms with businesses.”

Stolze spent a month speaking to corporations and discovered that while most of them were data-rich, they were also information poor. He moved into Amsterdam Startup Village, a ramshackle campus of repurposed shipping containers that’s tucked behind the University of Amsterdam, and began dropping into parties held by researchers at the School of Informatics.

The researchers told him that they could work for years on a particular problem, but still needed more data to improve their results. Stolze realised that what they needed was somebody to bridge the two worlds to help researchers put their algorithms to work. One of Aigency’s biggest challenges was to evaluate how machine learning could be used to streamline the operations of one of the world’s leading beer companies.

“We’re not talking about the sexy side of Heineken — all of the marketing or branding. No, we were involved in procurement, which for a lot of international companies is hell,” says Stolze. “It’s become normal for corporates to have offices all around the world, speaking different languages and using different CRM systems. That means there’s a lot of opportunity to simplify things with the right technology.”

Aigency worked with Heineken to overhaul how invoices are tracked and processed during its immense procurement operations. The firm has also enabled researchers to mine the sensor data from Tesla’s self-driving vehicles and, most recently, has been working with Holland’s largest commercial radio network to better understand the listening habits of their audience. Each project Aigency takes on requires the client to be realistic about the data they have access to and the problem they’re trying to solve.

“There’s so much hype and nonsense saying that AI will solve everything, but it’s not magic, it’s just math. When we talk to clients, we first try to fully understand the problem we’re solving. From there we can look at the available data and start finding the value that can be brought out by machine learning algorithms,” says Stolze. “Until the problem is properly defined, it can be really difficult to have down-to-earth conversations and explain what is and isn’t a problem AI can solve.”

Increasingly, Stolze has been looking at opening up its algorithms to more diverse clients. For example, tools that Aigency created in the commercial environment have now been donated to the Red Cross to be used by Missing Maps, a project that aims to protect human rights by collecting data on unmapped territories. Stolze believes that it’s important that Aigency’s algorithms are matched with the organisations that need them most, not just the highest bidder.

“Aigency acts as a matchmaker between startups, students and the corporates, but the more I talk to students the clearer it is that it’s not enough for them to just work with AI. They want to actually do something meaningful with it. So, we’ve started looking at how we can work with more NGOs,” says Stolze. “AI is too important to leave to the tech companies in Silicon Valley and we believe that NGOs and municipalities also deserve this super power.”

AI is an incredibly complicated field that so far is largely dominated by the tech giants. Most firms recognise the technology has enormous potential, but are content to put off understanding it until tomorrow. Aigency’s mission is to make sure that this super power is available today and for everybody.

Photo ‘Jim Stolze at the SingularityU The Netherlands Summit 2016’ by Sebastiaan ter Burg, used under CC BY / modified from original.


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