How does a test-and-learn mindset allow marketers to find success with Google's AI?

The selection is correct because adopting a test-and-learn mindset encourages teams to break down silos and quickly identify solutions by shifting the organizational focus from rigid, manual control to agile, data-driven experimentation. Google’s AI thrives on high-quality signals and broad optimization power, which are often hindered by fragmented departmental structures or "silos" that separate data, budget, and creative strategy. By fostering a culture that prioritizes testing—such as using Campaign Experiments to validate new bidding strategies or creative variations—marketers can move past internal assumptions and rely on objective performance data to see what truly resonates with their customers. This approach allows teams to iterate rapidly, failing fast on underperforming tactics while scaling successful AI-driven insights across the entire account, ultimately transforming marketing from a static cost center into a dynamic engine for business growth.