Connecting AI agents to enterprise knowledge
Survey of 300 executives finds only 34% of agentic AI projects reach production.
An MIT Technology Review Insights survey of 300 technology executives finds only about 34% of agentic AI projects reach production. Organizations that advance 61% of projects past pilot report stronger semantic knowledge capabilities. Data fragmentation was the top barrier to agent knowledge access (55%), while production leaders more often cited security and privacy (72%). Planned investments include ingestion pipelines, AI-ready APIs, retrieval-augmented generation, evaluation agents, and knowledge graphs. The report is custom sponsored content, not editorial.
- About 34% of agentic AI projects reach production on average.
- Production leaders move 61% of projects past pilot with stronger semantic knowledge.
- Data fragmentation was the most cited knowledge barrier, named by 55%.
- Planned spending covers pipelines, RAG, evaluation agents, and knowledge graphs.
From the original article
2 min read at technologyreview.com
For all the data that AI systems continually amass and analyze, enterprise AI agents often suffer from a curious shortcoming: a lack of knowledge. More than data, knowledge is the understanding of what the data means in the context of individual organizations. AI agents need this understanding to reason about situations, make decisions, and ultimately…
By MIT Technology Review Insights · technologyreview.com
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.