AWS
1.4 What makes agentic AI fundamentally different
Traditional generative AI is reactive – it answers when asked. Agentic AI is proactive: it plans, reasons, uses tools and executes multi-step workflows autonomously.
An agentic AI system requires five foundational components: a Model Hub & Gateway for centralised inference management; an Orchestration Layer for multi-agent coordination; Guardrails for safety and compliance; Observability for monitoring autonomous actions; Identity & Permissions to control what agents can access. This architectural demand – well beyond deploying a chatbot – helps explain why only 21 % of Nordic businesses feel ready for agentic AI.
“DEBATES ON SOVEREIGNTY AND STRATEGIC AUTONOMY ARE INTENSIFYING, BUT THE CRITICAL QUESTION IS HOW SOVEREIGNTY CAN STRENGTHEN COMPETITIVENESS”
AWS
Capability
Traditional GenAI( Chatbots / Copilots)
Agentic AI
Interaction
Single prompt > single response
Multi-step planning and execution
Tool Use None or predefined
Dynamic tool discovery and invocation
Memory Stateless( per conversation)
Autonomy Human initiates every action
Persistent memory across sessions
Agent initiates, human oversees
Scope Individual task assistance
End-to-end business process automation
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