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 Revenue Growth Management
A practical reference showing how AI agents drive revenue growth, how they run the loop, and a concrete worked example from goal to finish.
AI Agents for Revenue Management in Hospitality
Shows how an AI agent applies revenue management logic in hospitality, including goal setting, planning, tool use, result checks, and handoff, with a concrete worked example.
AI Agents for Revenue Management
This reference shows a complete loop of an AI agent for revenue management, detailing goal handling, tool use, result checks, and hand-off, plus a concrete worked example.
AI Agents for Revenue Recognition in Finance
Shows a practical AI agent loop for revenue recognition in finance, detailing goals, tools, checks, and a concrete worked example from goal to decision.
AI Agents for Revenue Recognition
This page shows how AI agents manage revenue recognition tasks, detailing the goal-driven loop, required tools, decision points, and a concrete worked example from goal to completion.
AI Agents for Review Analysis in E-commerce
Shows how AI agents analyze product reviews, plan steps, call tools, verify results, and hand off for review in e-commerce settings.
AI Agents for Review Analysis
This page shows how an AI agent analyzes product or service reviews: goals, tools, loop, and a concrete worked example from goal to finish.
AI Agents for Review Response in Hospitality
This page describes goal-driven AI agents for responding to hospitality reviews, showing how they plan, call tools, verify results, and hand off when needed.
AI Agents for Review Response
A practical reference on how AI agents handle review responses, including goals, tool use, and a concrete worked example from goal to finish.
AI Agents for RFI Management in Construction
This page demonstrates a practical AI agent loop for RFI management in construction, detailing goal, planning, tool calls, results checks, and handoff with a worked example.
AI Agents for RFI Management
This page shows how AI agents manage RFIs by goal planning, tool use, checks, and handoff, with a concrete worked example of an RFI response cycle.
AI Agents for RFP Management in Procurement
Shows how AI agents execute end-to-end RFP management in procurement, from goal setting to tool orchestration and hand-off, with a concrete worked example.
AI Agents for RFP Management
A practical reference showing how an AI agent manages an RFP lifecycle, from goal to tool use, result checks, and hand-off, with a concrete worked example.
AI Agents for Ride Dispatch in Transportation and Mobility
Shows how ride-dispatch AI agents plan, execute, and hand off tasks in urban mobility, detailing tool use, decision points, and a concrete worked example from goal to finish.
AI Agents for Ride Dispatch
This reference shows how a goal-driven AI agent for ride dispatch plans routes, calls tools, checks results, and decides to finish or hand off with a concrete worked example.
AI Agents for Rights Management in Media and Entertainment
Shows how a goal-driven AI agent handles rights management tasks in media and entertainment, including planning, tool use, result checks, and hand-off in a concrete worked example.
AI Agents for Rights Management
This page shows how an AI agent handles rights management tasks, from goal to execution, including planning, tool use, verification, and hand-off.
AI Agents for Risk Assessment in Insurance
This page shows how risk assessment AI agents operate in insurance, detailing goals, planning, tools, and a concrete worked example of a risk evaluation run.
AI Agents for Risk Assessment
A practical reference showing how risk assessment AI agents plan, call tools, interpret results, and stop, with a concrete worked example of a risk assessment run.
AI Agents for Risk Assessments in Legal and Compliance
Shows how a goal-driven AI agent conducts risk assessments in legal and compliance, from goal receipt through planning, tool calls, result checks, to final decision.
AI Agents for Risk Assessments
A practical reference showing how an AI agent performs risk assessments, the loop it runs, and a concrete worked example.
AI Agents for Risk Management Companies
This page shows how to deploy an AI agent for risk management firms, detailing ownership, permissions, and gradual scope growth through trust and governance.
AI Agents for Risk Management
A practical reference showing risk management AI agents: goals, tool use, loop flow, and a concrete worked example from goal to finish.
AI Agents for Risk Reporting in Capital Markets
This page describes how an AI agent performs capital markets risk reporting, detailing the goal–plan–action loop and 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.