Agentic AI · Anthropic · AI Agent · Claude · Google · MIT Technology Review
Data leaders detect it easier to achieve agent scale and speed
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Two-thirds of data laggards say legacy data systems limit AI agent scaling (66%) and prevent agents from making decisions at speed (68%).
Key facts
- Two-thirds of data laggards say legacy data systems limit AI agent scaling (66%) and prevent agents from making decisions at speed (68%)
- Within two years, 100% of respondents plan to be using agentic AI, with 69% expecting to use it widely
- Across all the surveyed organizations, AI only has access to an average of 45% of company data
- By contrast, 100% of the data leaders trust their agents’ decisions, a strong indicator that reliable AI requires a reliable data foundation
Summary
Agentic AI places considerable new demands on enterprise data systems. As AI agents become embedded more widely in enterprise operations, the need to overcome the restrictions of legacy data systems grows more urgent. This report, based on a survey of 300 data and technology executives, explores how legacy systems are limiting the effectiveness of AI agents in many organizations. Few companies currently provide agentic AI with ample access to enterprise data. Across all the surveyed organizations, AI only has access to an average of 45% of company data. Trust in agent decisions is a reflection of data readiness.