Gary Drenik

Employee using AI In a difficult business environment, artificial intelligence can look like an obvious answer for executives seeking faster work, lower costs and new efficiencies.

New research indicates a significant shift in consumer perception, where the payment experience now dictates whether customers feel truly understood by a brand. Nuvei's "How America Pays" study reveals 57% of consumers choose payment methods based on purchase context, with many regularly switching. This fragmentation means businesses can no longer assume a single "preferred" payment, as preferences vary by age, device, and transaction type. Crucially, 49% expect their preferred option, and 37% will abandon a purchase if it's absent, highlighting revenue-denting consequences. Payments have become a vital trust signal; 55% trust the payment method more than the retailer, and 38% judge retailers based on available options. This trend extends to agentic commerce, where AI must still reflect customer payment preferences. Businesses must move beyond optimizing for conversion, recognizing that the payment experience is now where customer perceptions are formed and trust is built.

Agentic AI As the initial excitement around artificial intelligence settles, businesses are taking a closer look at how these tools perform in the real world.

AI answer engines are the new entry point for brand trust. Marketers have followed the north star of search engine optimization (SEO) for

Organizations have embraced enterprise AI with remarkable speed and aggressive investment. Preparing the data behind it, however, has proven to be far more complex.

The gulf between enterprise AI spending and adoption is expanding. At the same time, an emerging trend is driving AI pricing. Capacity is up, costs are going down.

Artificial Intelligence As every business pushes for growth, companies are expanding into new markets, chasing new customers, and making decisions at a pace unthinkable a decade ago.

Nobody sets out to deploy an AI agent hoping it fails. Three years into the enterprise AI race, it’s happening at scale.

Nobody sets out to deploy an AI agent hoping it fails. Three years into the enterprise AI race, it's happening at scale.

There is a version of this story that executives have already heard: AI tools are producing more information than ever, much of it converging toward the same conclusions.