What is the difference between agentic AI and generative AI
What is the difference between agentic AI and generative AI rests on agency versus creation. Generative AI is a content engine: when prompted, it produces text, images, code, or audio and then stops. Agentic AI is an autonomous actor: it perceives streaming data, plans steps, calls external tools, and executes tasks—often looping until a goal is met. Generative models rely on large language or diffusion networks to predict the next token or pixel; agentic systems wrap those models inside planners, memory stores, and safety layers so they can, for example, replenish inventory, email prospects, or adjust ad bids without human nudges. Risk stacks differ: generative AI battles hallucinations and copyright issues, while agentic AI adds operational hazards like mis-execution and compliance breaches, demanding robust guardrails and human-in-the-loop approvals. In modern workflows, generative AI supplies rich content while agentic AI orchestrates actions, together forming end-to-end intelligent solutions.
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