As marketing becomes more directly tied to revenue goals, the ability to measure and report on its impact has declined. Some of that can be attributed to signal loss as the industry moves away from third-party tracking to more privacy-safe identifiers. Today’s audiences are also spread across multiple channels and devices. This makes it harder to track the customer journey and attribute results to specific marketing efforts.

A scrappy Chinese startup disrupts the AI hierarchy with a lean, open-source model, challenging Big Tech’s costly infrastructure and rewriting the rules of AI competition.

While AI adoption could save employees significant time, most still see it as a draft generator—helpful, but far from a finished product.

The AI agent interacts with the internet like a human and could replace personal assistants—but its data storage and cost implications loom large.

As genAI expands beyond chatbots, app categories like banking and messaging could see AI-driven disruption, reshaping mobile habits and spending trends

In-store, consumers want experiences that engage their senses, while online, they’re interested in generative AI (genAI) tools that can help them research products. Plus, young men in the South lead in fast-food consumption, retail leaders lean on loyalty to boost growth, and holiday spending remained in check (for the most part).

US hospitals use predictive AI tools, but many use biased data: Most AI models make recommendations based on homogenous data samples, which could actually harm many patients. But more regulatory oversight of healthcare AI isn’t guaranteed to happen in the near term.