What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously plan, reason, and take actions to achieve goals with minimal human oversight. Unlike chatbots that respond to prompts, AI agents can browse the web, execute code, call APIs, manage workflows, and make decisions independently.
In 2026, agentic AI is the dominant trend in enterprise AI adoption. Companies are deploying AI agents for customer support, code generation, data analysis, and process automation. Multi-agent systems — where multiple AI agents collaborate — are emerging for complex workflows.
The key challenge with agentic AI is governance: when an AI agent makes a decision autonomously, who is liable? Richard Ewing's analysis of the AI liability gradient shows that as agent autonomy increases, organizational liability increases non-linearly.
Why It Matters
Agentic AI promises massive productivity gains but introduces new governance, liability, and cost risks. Organizations deploying AI agents without proper oversight frameworks risk regulatory, legal, and financial consequences.
Frequently Asked Questions
What is agentic AI?
Agentic AI is artificial intelligence that can autonomously plan, reason, and take actions to achieve goals — going beyond simple chatbot responses to independently execute complex workflows.
Is agentic AI safe?
Agentic AI requires robust governance frameworks. Without proper oversight, AI agents can make costly mistakes, create liability, and take actions that conflict with organizational goals.
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Richard Ewing is a Product Economist and AI Capital Auditor. He helps companies translate technical complexity into financial clarity.
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