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 CSRD Compliance in ESG and Sustainability
This reference shows how AI agents execute CSRD compliance tasks in ESG and sustainability, detailing goals, tools, and stopping points with a concrete worked example.
AI Agents for CSRD Compliance
Demonstrates an AI agent loop for CSRD compliance, detailing goal handling, tool use, checks, and a concrete worked example across data gathering, assessment, and reporting.
AI Agents for Curriculum Design in Education
This page shows how an AI agent plans, calls tools, and iterates to design curriculum outlines, assess learning goals, and adjust content with human oversight.
AI Agents for Curriculum Design
This reference shows how goal-driven AI agents design curricula by planning, executing tool calls, verifying outcomes, and handing off when appropriate, with a concrete worked example and clear operational boundaries.
AI Agents for Customer Billing in Energy and Utilities
Shows how goal-driven AI agents handle customer billing tasks in energy and utilities, including tool use, decision points, and a concrete worked example.
AI Agents for Customer Billing
A concise reference showing how an AI agent handles customer billing tasks, from goal to tool use to hand-off, with a concrete worked example.
AI Agents for Customer Care in Telecommunications
This page defines the AI agent loop for handling customer care in telecommunications, detailing roles, required tools, and a concrete worked example from goal to finish.
AI Agents for Customer Care
Shows how AI agents handle customer care tasks end-to-end, including goal setting, planning, tool use, result checks, and handoff in a concrete worked example.
AI Agents for Customer Churn Prevention in Banking
Shows how a goal-driven AI agent detects at-risk customers, plans actions, calls tools, and hands off when needed in banking churn prevention.
AI Agents for Customer Churn Prevention
Shows the AI agent loop for preventing customer churn, including goals, tools, signals, and a concrete worked example.
AI Agents for Customer Feedback Analysis in Customer Service
This reference shows how a goal-driven AI agent analyzes customer feedback, what tools it uses, and a concrete worked example from goal to decision.
AI Agents for Customer Feedback Analysis
This page demonstrates a goal-driven AI agent that analyzes customer feedback, plans actions, calls tools, verifies results, and stops or hands off when the objective is achieved, with a concrete worked example.
AI Agents for Customer Feedback Synthesis in Product Management
This page shows how AI agents perform customer feedback synthesis in product management, detailing goal-driven loops, required tools, and a worked example that ends with a concrete decision.
AI Agents for Customer Feedback Synthesis
This page shows how AI agents extract, normalize, and synthesize customer feedback into actionable insights, detailing the goal-driven loop, required tools, and a concrete worked example for teams.
AI Agents for Customer Notifications in Field Service
A practical reference showing how an AI agent manages customer notifications in field service, including goal-driven flow, tool calls, checks, and a concrete worked example.
AI Agents for Customer Notifications
This page shows how AI agents manage customer notification workflows, the loop from goal to finish, required tools, and a concrete worked example.
AI Agents for Customer Onboarding in Insurance
Shows how a goal-driven AI agent handles customer onboarding in insurance, from data intake to policy issuance, with checks, tool calls, and a final handoff.
AI Agents for Customer Onboarding in Software and SaaS
This page shows how goal-driven AI agents handle customer onboarding in software and SaaS, including planning, tool use, checks, and hand-off to humans when needed.
AI Agents for Customer Onboarding
A practical reference showing how AI agents handle customer onboarding goals, tool use, and decision points, with a concrete worked example from goal to finish.
AI Agents for Customer Rebooking in Travel and Airlines
Shows how AI agents handle customer rebooking in travel and airlines, from goal to final action, with a concrete worked example and required controls.
AI Agents for Customer Rebooking
Shows how an AI agent handles customer rebooking tasks end to end, including goal-driven planning, tool use, result checks, and handoff.
AI Agents for Customer Retention in Insurance
A practical reference showing how an AI agent drives customer retention in insurance, including goal planning, tool usage, and a concrete worked example.
AI Agents for Customer Retention
Reference page showing how goal-driven AI agents manage customer retention tasks, tools used, and a concrete worked example from identification to handoff.
AI Agents for Customer Segmentation in Retail
Shows how an AI agent plans, calls tools, and validates results to deliver customer segment insights and actions in retail.
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.