Data Strategy

LLMs can make sophisticated pricing recommendations, but effective use requires well-crafted prompts and an understanding of the tools’ limitations.

From the AI bubble to GenAI’s rise as an organizational tool, these are the 2026 AI trends to watch. Explore new data and advice from AI experts.

As AI use widens, enterprise-level impact is still uneven, so the edge now is careful design and accountable oversight

The real data quality breakthrough happens when companies transition to the third mode, where errors are prevented at the source. But this shift requires a major change in mindset, in which every employee recognizes that they are both a data creator and a data customer and starts acting like it.

Data-efficient AI techniques are emerging — and that means you don’t always need large volumes of labeled data to train AI systems based on neural networks.