After an initial AI microdegree, I spent the past academic year at HOWEST University of Applied Sciences diving deeper again into algorithms, optimisation methods and the very latest AI applications, complemented by guest lectures from ML6 and IBM consultants.
Artificial intelligence is a field evolving so rapidly that continuous learning is not optional, but a prerequisite. My decision to fully commit to AI is confirmed every day. Theoretical knowledge is of course a basic requirement, but the most valuable learning happens when that knowledge can be tested against concrete practical use cases, when there is room to experiment, make mistakes and adjust. It has already produced inspiring insights into areas including GenAI, computer vision, time-series forecasting and recommender systems, ready to be translated into measurable business impact.
That brings an entirely different challenge. The step from idea to impact requires more than AI expertise alone: business requirements, feasibility studies, data quality, governance and compliance frameworks, infrastructure, technical integrations into existing processes, change management and budgets determine whether an AI initiative actually delivers a return. Experience on both the strategic and technical side, gained across various projects, helps put those puzzle pieces in place quickly and effectively without losing sight of the bigger picture.
A complex challenge, but one that only increases my enthusiasm to keep building that knowledge and experience, to explore where artificial intelligence can already make a difference today, and where tomorrow we can make the seemingly impossible possible.
