Across a business, any number of AI platforms, systems, and tools may be at work simultaneously—for example, AI-powered customer platforms, conversational assistants, and workflow and process automation tools. Each one is sophisticated, advanced, and quick to respond. But, when set to work, the outcomes and actions that emerge may be wrong, confused, or lacking a proper understanding of the business.
Many organizations find themselves in this situation—and it could be one of key reasons they struggle to extract returns on their AI investments. An MIT Technology Review Insights poll finds that while every organization surveyed is using AI today to some degree, fewer than one in five (16%) are extracting transformative value from their deployments. The largest percentage of respondents (40%) say they are seeing moderate gains in specific tasks or teams, while 21% report meaningful gains, leaving 23% that are seeing minimal returns or none at all.
Companies are mostly still piloting AI use cases (according to 38% of respondents) or using it to assist employees’ work with tools like co-pilots or chat assistants (35%). Just 12% of enterprises have AI agents in production and 3% say they are using AI to do most of the work in key processes. It’s just not really useful in most companies today.” The missing layer, Sankar says, is context, or how well AI understands a business.
A context layer is the architectural infrastructure that sits between an organization’s business systems (for example, systems of record and data, and its AI platforms). It translates enterprise intelligence into governed, machine-usable context for AI agents or models and helps knowledge compound. This content was produced by Insights, MIT Technology Review’s custom content arm, not its editorial staff.
It was researched and written by humans, with any AI tools that may have been used limited to production processes under human oversight. Ten years after AlphaGo’s match against Go champion Lee Sedol, today’s AI still isn’t tapping into the machinery that made that win possible. An exclusive interview with Nick Cammarata, the researcher whose 26,000-word viral blog post has AI safety folks celebrating.
Breathless claims about AGI and new capabilities fall apart pretty quickly under scrutiny. Surveillance towers, increasingly powered by AI, promised faster responses to crossings. Our investigation of deaths near the towers found they are failing to deliver.
Extract — continue reading at the source.
