What is AI Agent?
The distinction between an AI assistant and an AI agent is action. An AI assistant answers questions; an AI agent changes things. A KYC agent doesn't just tell you what documents are needed — it checks what you've submitted, queries the identity verification API, flags mismatches, and updates the customer record. That action loop — perceive, decide, act, observe result, repeat — is what makes something an agent rather than a chatbot. Specialist agents built for a single domain (claims, compliance, procurement) consistently outperform general-purpose agents, because narrow scope means tighter guardrails, faster tool selection, and lower hallucination rates.
Enterprise AI agent deployments require careful attention to three production concerns that research demos rarely surface. First, failure modes: what does the agent do when a tool call times out, an API returns an unexpected schema, or a downstream system is unavailable? Second, context management: how does the agent maintain coherent state across a workflow that might span 20+ tool calls? Third, handoff: when does the agent escalate to a human, and how does that handoff preserve context so the human doesn't have to start from scratch?
Also known as: Agentic AI, AI Assistant
Key Points
Core idea
Every AI agent cycle follows the same loop: perceive inputs (documents, API responses, user messages), decide the next action using the LLM, execute that action via tool use, then observe the result and decide again.
Why it matters
Narrowly scoped agents built for a specific workflow outperform general-purpose agents. A claims agent has tighter guardrails, faster tool selection, and demonstrably lower error rates.
Enterprise use
Complex enterprise workflows decompose into multiple specialist agents: one for document extraction, one for compliance checks, one for customer communication. An orchestrator coordinates them.
How AI Agent works
Define the purpose, inputs, and success criteria that AI Agent must support.
Apply AI Agent in the relevant workflow while recording its inputs, configuration, and outputs.
Evaluate the result against representative data, operational constraints, and human review before expanding production use.
Multi-agent orchestration for enterprise workflows.
Fluid AI deploys specialist AI agents that coordinate on complex workflows. Handoffs are automatic. Every agent is auditable, integrates with SAP, Salesforce, and core banking, and runs inside your data center.
Explore Autonomous AgentsTopics Covered
- AI agent enterprise deployment
- specialist AI agents
- AI agent vs chatbot
- AI agent workflow
- autonomous agent software
- AI agent architecture
- building AI agents for business
- AI agent tool use