Until recently, artificial intelligence and machine learning were the domain of large tech firms. But new developments – such as easily accessible user platforms – are making this technology available to a much wider audience. Jan Veldsink, core lecturer in AI and Cyber at Nyenrode Business University and Artificial Intelligence Lead at Rabobank, has made it his mission to integrate AI and machine learning into the corporate mindset. This is his focus in the Compliance and Fraud departments at Rabobank, where he works on solutions with AI and machine learning and provides training to staff. From July 8 through 11, Veldsink will serve as chairman during the Machine Learning Summer School organized by Nyenrode and BigML.
Many companies wonder how they should approach machine learning and AI, and whether this is a technical or business affair. For Jan Veldsink, the answer is clear: “As far as I'm concerned, machine learning and AI are matters of business, not IT. That requires quite a shift in thinking.”
How does a company achieve this? Veldsink sees those in management playing a key role: “People in business management have to understand what machine learning is and how it differs from what they have been doing thus far in the realm of traditional software development. That is why we are organizing the Machine Learning Summer School, with a specific focus on this topic in a business context. You also have to take a careful look at the competences within your organization if you want to introduce machine learning into the mindset of your employees. How should you develop your teams, and should you perhaps hire new people?”
Product development, service departments, legal affairs, administration: all of these areas can reap the benefits of what machine learning has to offer. In order to reach everyone, including the people without a technical background, artificial Intelligence and machine learning must tie in with the work they perform. Veldsink: “Talk to people about their job. I recently trained 20 auditors to incorporate machine learning into their work. The training was partly about the technology, but the main focus was on the data that they know inside and out, and how they can do smarter things with it.”
In this new way of thinking, data is not a goal in itself, but a tool for making better and faster business decisions. The models that can be built with machine learning improve as new data is fed into them, allowing businesses to quickly respond to changes. “With machine learning, you can use data to create new software without involving a programmer,” Veldsink says. “That saves a huge amount of time and money. You really don’t need to have millions of data points, either. You can already start learning from your data with just a few hundred customers.”
AI is a moving train that can’t be stopped; this much is clear. Where will we be ten years from now? Jan Veldsink predicts that all companies will soon be implementing machine learning on a large scale. “Every business will be faced with this technology, whether you're in financial services, a corporate context or an SME. All software will include AI and even be written by AI.”