Agentic AI
An AI system that, building on foundation model and physical AI capabilities, can autonomously decompose goals, perform multi-step planning, and invoke external tools. Agentic AI systems are designed to complete complex, long-horizon task sequences without requiring step-by-step human instruction throughout execution.
Core Facts
Timeline (last 90 days)
Agentic AI in the EU is moving from proof of concept to scaled deployment, covering a broad group ranging from large enterprises to small and medium-sized enterprises.
Analysts believe that the adoption rate of Agentic AI among EU enterprises will continue to climb for some time to come.
The implementation of Agentic AI in the EU is concentrated in high-value scenarios such as customer operations, supply chain and logistics, and compliance and risk control.
A replenishment agent whose sole objective is to minimize inventory costs may, without violating any rules, compress safety stock to a level that causes stockouts, because stockout losses were not incorporated into the optimization objective.
Resolving goal misalignment typically requires introducing constraints, human-in-the-loop review checkpoints, and continuous monitoring of system behavior, rather than relying solely on the model's own understanding capabilities.
The white paper argues that agent permissions should dynamically converge based on task context, rather than inheriting the user's full permissions in a one-time grant.
The white paper argues that the entire authorization delegation chain from human users to agents at all levels needs to be expressed in a cryptographically verifiable manner.
The white paper argues that agents should have their own independently verifiable identity credentials, rather than simply reusing user credentials.
Rule-based alert correlation systems can only match predefined patterns, whereas intelligent agents can handle never-before-seen fault combinations in an open search space
All Facts (10)
AI智能体具备三个关键能力：任务规划、工具调用、记忆与上下文管理
80%UnverifiedThe implementation of Agentic AI in the EU is concentrated in high-value scenarios such as customer operations, supply chain and logistics, and compliance and risk control.
50%UnverifiedA replenishment agent whose sole objective is to minimize inventory costs may, without violating any rules, compress safety stock to a level that causes stockouts, because stockout losses were not incorporated into the optimization objective.
50%UnverifiedResolving goal misalignment typically requires introducing constraints, human-in-the-loop review checkpoints, and continuous monitoring of system behavior, rather than relying solely on the model's own understanding capabilities.
50%UnverifiedThe white paper argues that the entire authorization delegation chain from human users to agents at all levels needs to be expressed in a cryptographically verifiable manner.
50%UnverifiedThe white paper argues that agent permissions should dynamically converge based on task context, rather than inheriting the user's full permissions in a one-time grant.
50%UnverifiedThe white paper argues that agents should have their own independently verifiable identity credentials, rather than simply reusing user credentials.
50%UnverifiedRule-based alert correlation systems can only match predefined patterns, whereas intelligent agents can handle never-before-seen fault combinations in an open search space
50%UnverifiedAnalysts believe that the adoption rate of Agentic AI among EU enterprises will continue to climb for some time to come.
50%UnverifiedAgentic AI in the EU is moving from proof of concept to scaled deployment, covering a broad group ranging from large enterprises to small and medium-sized enterprises.
50%