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 Risk Reporting in Risk Management
This page shows how AI agents perform risk reporting tasks, including goal-driven planning, tool usage, result verification, and hand-off in a risk management setting.
AI Agents for Risk Reporting
This page documents how an AI agent for risk reporting operates: goals, planning, tool use, result validation, and hand-off, plus a concrete worked example from goal to finish.
AI Agents for Roadmap Planning in Product Management
This reference shows how AI agents perform goal-driven roadmap planning for product management, detailing loop steps, tool calls, checks, and a concrete worked example from goal to decision.
AI Agents for Roadmap Planning
A practical reference showing how AI agents plan product roadmaps, execute steps, and verify results with a concrete worked example.
AI Agents for Robotics Orchestration in Warehousing
This page shows how AI agents orchestrate robotics in warehousing, detailing goals, tool calls, loop logic, and a concrete worked example from target to task completion.
AI Agents for Robotics Orchestration
A practical reference showing how a goal-driven AI agent orchestrates robotics tasks, the tools it calls, and a concrete worked example from goal to finish.
AI Agents for Root Cause Analysis in IT Operations
AI agents for root cause analysis in IT operations demonstrate goal-driven loops, tool use, and handoffs to isolate incidents and guide fixes with auditable steps.
AI Agents for Root Cause Analysis in Manufacturing
This page explains how AI agents perform root cause analysis in manufacturing, detailing goals, tools, loop steps, and a concrete worked example for reference.
AI Agents for Root Cause Analysis
Shows how an AI agent performs root cause analysis, from goal definition to tool use and decision to finish, with a concrete worked example.
AI Agents for Route Optimization in Logistics
This page demonstrates an AI agent that plans, tests, and commits to a logistics route plan, with a concrete worked example showing decision points and human handoff.
AI Agents for Route Optimization
This page defines a goal-driven AI agent loop for route optimization, lists required tools, and shows a worked example from goal to finish.
AI Agents for Royalty Processing in Media and Entertainment
This page shows how royalty processing agents operate in media and entertainment, including planning, tool calls, verification, and hand-off, with a concrete worked example.
AI Agents for Royalty Processing
A reference page showing how AI agents can process royalties: goals, tools, loop, and a concrete worked example from goal to hand-off.
AI Agents for Runbook Execution in IT Services and MSP
This reference expands runbook execution in IT services and MSP, detailing agent loops, tool calls, controls, and a worked example aligned to real runbook environments.
AI Agents for Runbook Execution
A practical reference showing how AI agents execute runbooks: goal handling, planning, tool calls, result checks, and handoff with a concrete worked example.
AI Agents for Safety Compliance in Construction
A practical reference showing how an AI agent handles safety compliance tasks in construction, from goal to tool use and handoff, with a concrete worked example.
AI Agents for Safety Compliance
This page shows how AI agents for safety compliance operate: goal-driven loops, tool calls, checks, and when to stop, plus a concrete worked example with field mappings, governance steps audits.
AI Agents for Safety Data Sheet Generation in Chemicals
This page defines a practical AI agent loop for safety data sheet generation in chemicals, detailing goals, tools, stopping criteria, and a full worked example.
AI Agents for Safety Data Sheet Generation
This reference shows how a goal-driven AI agent generates safety data sheets, detailing goals, tools, loop, and a concrete worked example.
AI Agents for Safety Monitoring in Mining and Metals
A practical reference showing how AI agents run safety monitoring tasks in mining and metals, with a concrete worked example.
AI Agents for Safety Monitoring
Overview of goal-driven AI agents for safety monitoring, how they run in a loop, and a concrete worked example showing planning, tool calls, checks, and handoff.
AI Agents for Safety Stock Planning in Supply Chain
This reference shows how AI agents conduct safety stock planning in supply chains, detailing the goal loop, tool calls, checks, and a concrete worked example for practitioners.
AI Agents for Safety Stock Planning
This page demonstrates how AI agents handle safety stock planning, detailing the goal loop, tool use, checks, and a concrete worked example for inventory decision-making.
AI Agents for Sales Companies
This page presents how to design and deploy an AI agent for a sales company, detailing initial deployment, ownership, permissions, and gradual scope expansion as trust grows within the organization.
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.