AI Agents
See what AI agents can do for your industry or process: the jobs they take on, how each agent runs, and a worked example with sample data.
Direct Answer
AI agents are software given a goal instead of a fixed script: they plan steps, call tools, check the results, and stop or hand off to a person when a decision carries risk. Pick your industry or process below to see what an agent can do, how it runs, and a worked example.
AI Agents for Agent Assist in Customer Service
A practical reference showing how an agent assist system works in customer service, with a concrete worked example from goal to finish and notes for deployment.
AI Agents for Agent Assist
This page shows how an AI agent for agent assist operates, including goal handling, planning, tool use, validation, and when to stop, with a concrete worked example.
AI Agents for Agri Input Recommendations in Agriculture
This reference shows how AI agents propose agronomic input plans, execute actions, verify outcomes, and hand off when human review is needed.
AI Agents for Agri Input Recommendations
This page defines how an AI agent recommends agricultural inputs by goal-driven planning, tool use, result verification, and hand-off, with a concrete worked example.
AI Agents for Agriculture Companies
This reference shows how an agriculture company deploys a goal-driven AI agent, its ownership, permissions, and growth of scope through trust, with a concrete worked example at the company level.
AI Agents for Agriculture
This page shows how an AI agent can manage crop health, irrigation, pest control, and harvest planning through goal-driven loops with concrete, domain-specific tools and a worked example.
AI Agents for AIOps in IT Operations
This reference shows how an AI agent can operate in AIOps, including goal handling, tool use, result checks, and handoff, with a concrete worked example.
AI Agents for AIOps
This page shows how AI agents operate in AIOps, detailing goal-driven loops, tool calls, result checks, and when to stop, plus a worked example.
AI Agents for Aircraft Maintenance in Travel and Airlines
This page explains how goal-driven AI agents handle aircraft maintenance tasks in travel and airlines, detailing the loop, tools, and a concrete worked example.
AI Agents for Aircraft Maintenance
A practical reference showing how AI agents plan, execute, and finish tasks in aircraft maintenance workflows with a concrete worked example that reflects real industry data flows.
AI Agents for Airport Operations in Travel and Airlines
This page defines how AI agents operate in airport logistics, outlining goals, tools, and a concrete worked example of an agent running from plan to action.
AI Agents for Airport Operations
A practical reference showing how AI agents drive airport operations, the loop from goal to tool use to decision, with a concrete worked example.
AI Agents for Allocation Planning in Supply Chain
This page shows how an AI agent performs allocation planning in supply chains, detailing the loop from goal to tool calls to decision and hand-off, with a concrete worked example.
AI Agents for Allocation Planning
This page explains how AI agents perform allocation planning, showing the goal-driven cycle, tools used, checks, and a concrete worked example from goal to hand-off.
AI Agents for Alumni Engagement in Education
This page defines practical AI agent roles for alumni engagement in education, showing how goals are translated into plans, tools, checks, and handoffs with a concrete worked example.
AI Agents for Alumni Engagement
Shows how AI agents pursue goals, plan steps, call tools, evaluate results, and hand off, using alumni engagement as the topic.
AI Agents for AML Transaction Monitoring in Banking
Demonstrates an agent loop for AML transaction monitoring in banking, outlining goals, tools, checks, and a worked example of anomaly analysis and escalation.
AI Agents for AML Transaction Monitoring
This page shows how AML transaction monitoring AI agents operate, including goal planning, tool use, result checking, and handoff, with a concrete worked example from goal to finish.
AI Agents for Anomaly Detection in Data and Analytics
A practical reference showing how AI agents detect anomalies in data and analytics, including the loop, tools, and a concrete worked example from goal to finish.
AI Agents for Anomaly Detection
This reference shows how an anomaly detection agent plans, calls tools, validates results, and stops, with a worked example illustrating the loop from goal to finish.
AI Agents for API Integration in Software Engineering
Shows the AI agent loop for API integration in software engineering, including planning, tool use, checks, and a concrete worked example.
AI Agents for API Integration
This reference shows how AI agents execute API integration work, from goal to tool use, result checks, and hand-off, with a concrete worked example.
AI Agents for Appointment Booking in Small and Medium Businesses
This page shows how an AI agent for appointment booking in SMBs operates: goal-driven loop, tool calls, status checks, and a concrete worked example.
AI Agents for Appointment Booking
This page defines an AI agent workflow for appointment booking, detailing goals, tool calls, checks, and handoffs, plus a concrete worked example of a full agent run.
FAQ
What is an AI agent?
An AI agent is software given a goal rather than a fixed script. It plans steps, calls tools, checks the results, and either finishes or hands off to a person.
What is the difference between an AI agent and AI automation?
AI automation runs a defined process with AI at certain steps. An AI agent chooses its own next step toward a goal, which suits work where the path changes from case to case.
Which AI agent should a business build first?
Start with one narrow goal, read-mostly tool access, and a clear owner. Widen what the agent may do alone only after its logged runs show it can be trusted.