AI Intelligence Paradigms: Agents vs Agentic Systems. Transformative AI Intelligence emerges as organizations face a critical choice between traditional isolated AI agents and revolutionary networked agentic systems. Risk managers must prepare for a paradigm shift where collaborative AI intelligence could dramatically reshape problem-solving and strategic decision-making across industries.
Source : Post | LinkedIn
Quick Summary
AI Agents and Agentic AI represent fundamentally different approaches to problem-solving and intelligence.
Key Points
- AI Agents operate in isolation with sequential, task-specific workflows
- Agentic AI uses network connectivity and collective intelligence for complex problem solving
- The key difference is individual versus collaborative decision-making processes
Why It Matters
As AI evolves, understanding the distinction between isolated agent tasks and networked, coordinated intelligence becomes crucial for organizations. Agentic AI suggests more adaptive, emergent solutions that could revolutionize how complex problems are approached across industries.
