Most companies remain in the early stages of adopting artificial intelligence: 38% of respondents are piloting AI use cases, while 35% use copilots, chat assistants, or similar tools to support employees. Only 12% report having AI agents in production, and 3% say AI performs most of their key processes.
“There is a huge disconnect between the power of a model and how it can actually help an organization,” says Prukalpa Sankar, co-founder of Atlan. “For all real-world intents and purposes, artificial general intelligence already exists. It’s not really useful in most companies today.”
The missing context layer
Sankar says the missing piece is context: how well an AI system understands a particular business. The context layer is architectural infrastructure positioned between an organization’s business systems—including systems of record and data systems—and its AI platforms.
This layer transforms enterprise intelligence into context that managed machines, AI agents, or models can use to compound knowledge. “Without the context layer of AI, it’s like hiring the smartest intern in the world and throwing them blindfolded into your organization,” Sankar says.
This content was created by Insights, the custom content division of MIT Technology Review, and not by editorial staff. It was researched and written by humans, and any AI tools that may have been used were limited to production processes under human supervision.
Source: www.technologyreview.com
