Most organizations using AI are not getting transformative returns from it, according to an MIT Technology Review Insights poll. The poll found that 16% of surveyed organizations extract transformative value from their AI deployments. Another 40% report moderate gains in specific tasks or teams, 21% report meaningful gains, and 23% report minimal returns or none.
The poll also found that 38% of respondents are still piloting AI use cases, and 35% use AI to assist employees with tools such as co-pilots or chat assistants. Only 12% have AI agents in production, and 3% use AI to do most of the work in key processes.
Prukalpa Sankar, co-founder of Atlan, attributes the gap to context. She says there is a "big gap between what the models are capable of and how the models are actually being useful inside organizations." Sankar describes a context layer as architectural infrastructure that sits between business systems and AI platforms. In her account, it translates enterprise information into governed, machine-usable context for AI agents or models. She says that without it, AI tools lack a proper understanding of the business. In her words, "it's almost like you're hiring the smartest intern in the world, blindfolding them, and throwing them into your organization."
The source is a sponsored piece produced by MIT Technology Review's Insights custom content arm, not its editorial staff.