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 Personalized Upselling in Hospitality
This page shows how AI agents handle goal-driven personalized upselling in hospitality, detailing the loop from goal receipt to plan, tool calls, result checks, and handoff or finish.
AI Agents for Personalized Upselling
This reference explains how an AI agent conducts personalized upselling work, including goal planning, tool calls, result checks, and final handoff with concrete examples that stay within the workflow loop.
AI Agents for Pest and Disease Detection in Agriculture
This page shows the AI agent loop for detecting pests and diseases in crops, from goal to tool use to decision, with a concrete worked example.
AI Agents for Pest and Disease Detection
This page defines a practical AI agent loop for pest and disease detection, detailing goals, tools, checks, and a concrete worked example within agricultural and field-science contexts.
AI Agents for Pharma and Life Sciences Companies
Shows how to deploy and scale a pharma and life sciences AI agent from pilot to broad enterprise use, including ownership, permissions, and governance.
AI Agents for Pharma and Life Sciences
This page defines AI agents for pharma and life sciences, showing goal-driven loops, required tools, and a concrete worked example.
AI Agents for Pharmacovigilance in Pharma and Life Sciences
A practical reference showing how AI agents handle pharmacovigilance goals, tool usage, and decision points, with a concrete worked example of end-to-end agent execution in life sciences.
AI Agents for Pharmacovigilance
This page shows how pharmacovigilance AI agents plan, execute, and verify safety signal workflows with concrete tool calls and a worked example.
AI Agents for Pharmacy Operations in Hospitals
Shows how AI agents manage hospital pharmacy workflows, plan actions, call tools, verify results, and hand off when needed in a practical, goal-driven loop.
AI Agents for Pharmacy Operations
This page shows how a goal-driven AI agent can optimize pharmacy operations from order intake to fulfillment, with a concrete worked example and clear stopping rules.
AI Agents for Phishing Analysis in Cybersecurity
Shows how a goal-driven AI agent analyzes phishing signals, maps tasks, calls tooling, and delivers a verified verdict with a worked example.
AI Agents for Phishing Analysis
This reference explains AI agents for phishing analysis, detailing goal-driven loops, required tools, and a concrete worked example of handling a phishing incident from intake to resolution.
AI Agents for Pick Path Optimization in Warehousing
Shows how a goal-driven AI agent plans and executes a pick path optimization task in a warehouse, including tool use, checks, and a concrete worked example.
AI Agents for Pick Path Optimization
This page shows how AI agents handle pick path optimization, detailing the agent loop, required tools, and a concrete worked example for warehouse routing.
AI Agents for Pipeline Management in Sales
A practical reference showing how AI agents manage a sales pipeline, including goal-driven planning, tool calls, results checks, and a concrete worked example.
AI Agents for Pipeline Management
Shows how AI agents manage pipeline workflows, plan steps, call tools, verify results, and hand off when appropriate, with a concrete worked example.
AI Agents for Pipeline Monitoring in Oil and Gas
This page shows how an AI agent monitors pipelines, plans actions, calls tools, and hands off when needed, with a concrete worked example.
AI Agents for Pipeline Monitoring
Shows how an AI agent monitors a pipeline, plans actions, calls tools, checks results, and hands off when done, with a concrete worked example.
AI Agents for Plan Recommendations in Telecommunications
This reference shows how an AI agent plans and recommends optimal telecom plans, with a concrete worked example and the loop from goal to hand-off.
AI Agents for Plan Recommendations
This reference explains how AI agents generate, validate, and present plan recommendations, including the decision loop and a worked example of goal-driven planning in practice.
AI Agents for Plant Maintenance in Chemicals
Shows how a goal-driven AI agent can manage plant maintenance tasks in a chemical facility, including planning, tool calls, result checks, and hand-offs with a concrete worked example.
AI Agents for Plant Maintenance
This page describes how AI agents execute goal-driven plant maintenance tasks, including a worked example from goal to finish operationally.
AI Agents for Policy Administration in Insurance
This page shows how a policy administration AI agent plans, executes tool calls, verifies results, and finishes or hands off in an insurance policy workflow.
AI Agents for Policy Administration
A practical reference showing how AI agents handle policy administration tasks, from goal to tool use to hand-off, with a concrete worked example.
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.