Agents are the new promise. Autonomous, fast, scalable, and finally able to fix the mess underneath. Meanwhile pilots that never scaled keep piling up, and the gap between AI experimentation and real business transformation keeps growing.
Maria's argument is that agents do not close that gap. They widen it. A human working with unreliable data makes mistakes slowly and visibly. An agent makes them fast, silently, and many times over. What determines whether AI scales is not the sophistication of the technology, it is whether anyone in the business owns the data it runs on and the decisions it makes.
Drawing on a decade on the business side of data and AI transformations — from digital strategy, to building a data and analytics function with a double-digit million euro annual value pipeline, to designing the target operating model for business data governance at global scale — she shows what has to change in the operating model before autonomy is worth having.