Dirk Luyckx interview on the potential of AI

When applying AI in a business setting, there are different levels of maturity. The initial stage, often referred to as “experimentation,” involves using AI tools for tasks such as generating presentation ideas or matching CVs with job descriptions.

The next level involves leveraging AI on proprietary company datasets, which remains relatively straightforward. However, as organizations progress, they often seek to automate business processes using AI. At this stage, data quality becomes crucial. Ensuring high data quality requires robust data governance, a well-defined data architecture, and a data platform capable of implementing necessary changes. Ultimately, automating the data platform is essential to focus on true value creation.