Customers must decide whether to build or buy new AI tools, or use the vendor tools they already have, all while training their teams and anticipating future pricing changes, Barbosa suggests. “That’s a lot to sort through, and it slows adoption down even when the capability itself is ready,” she adds.

Software vendors need to aim to embed AI into their products in a way that feels effortless, is part of the operating model that customers already use, and intuitive enough that early adoption doesn’t require a big lift, Barbosa says.

But that’s only half the battle. Vendors also need to back their AI tools with structured, scaled adoption models that tie directly back to value realization and ROI, she adds. “Capability without that structure is where the gap shows up,” she says.