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 Menu Engineering in Food and Beverage
A reference page showing how AI agents plan, execute, and stop in menu engineering tasks, with a concrete worked example for data-driven menu optimization.
AI Agents for Menu Engineering
This page shows how AI agents for menu engineering operate, including goal-driven loop, tool calls, result checks, and a concrete worked example.
AI Agents for Merchandising in Retail
Shows how an AI agent iterates on merchandising goals, plans steps, calls tools, evaluates results, and finalizes or hands off with a concrete worked example and explicit role responsibilities.
AI Agents for Merchandising
Shows how merchandising AI agents plan, execute tool calls, check results, and stop, with a concrete worked example.
AI Agents for Meter Data Management in Energy and Utilities
Shows how an AI agent plans, calls tools, and validates results to manage meter data across the energy grid with a concrete worked example.
AI Agents for Meter Data Management
A practical reference showing how an AI agent manages meter data, from goal definition to tool use and decision stopping, with a concrete worked example.
AI Agents for Mine Planning in Mining and Metals
A practical reference showing how AI agents plan mine layouts, evaluate cuts, and hand off when decisions exceed defined thresholds in mining and metals projects.
AI Agents for Mine Planning
A practical reference showing how AI agents conduct mine planning tasks, from goal to plan, tool calls, results checks, and hand-off with a concrete worked example.
AI Agents for Mining and Metals Companies
This page shows how a mining company deploys a single AI agent, its ownership, permissions, and scoped expansion as trust grows, with a concrete worked example for governance.
AI Agents for Mining and Metals
This page shows the AI agent loop for mining and metals: goals, tool calls, results checks, and a concrete worked example from goal to finish.
AI Agents for Mission Planning Support in Defense and Aerospace
A practical reference showing how an AI agent plans, executes, and concludes a mission planning task in defense and aerospace.
AI Agents for Mission Planning Support
A practical reference showing how AI agents handle mission planning support, including goal-driven loops, tool use, checks, and a concrete worked example.
AI Agents for Model Risk Management in Risk Management
This page describes goal-driven AI agents for model risk management, detailing the loop, tools, and concrete worked example to guide implementation and governance.
AI Agents for Model Risk Management
AI agents for model risk management demonstrate a goal-driven loop: define risk objectives, plan steps, call data and validation tools, verify results, and hand off when criteria are satisfied.
AI Agents for Monitoring and Alerting in IT Services and MSP
This page shows how AI agents run monitoring and alerting tasks in IT services and MSPs, including goal-driven loops, tool use, and a concrete worked example expanded for clarity.
AI Agents for Monitoring and Alerting
A practical reference showing AI agents for monitoring and alerting: how they pursue goals, what tools they call, and a concrete worked example from goal to finish.
AI Agents for Mortgage Processing in Banking
This page defines a practical loop for mortgage processing agents, detailing goals, tool use, checks, and a concrete worked example end-to-end.
AI Agents for Mortgage Processing
A practical reference showing AI agents for mortgage processing: goals, tool use, decision points, and a concrete worked example from goal to hand-off.
AI Agents for Multi-echelon Planning in Supply Chain
This page shows how AI agents perform multi-echelon supply chain planning, including goal-directed looping, tool usage, result checks, and hand-off, with a concrete worked example for a practical deployment.
AI Agents for Multi-echelon Planning
This page shows how an AI agent handles multi-echelon planning from goal to action, including tool use, decision points, and a concrete worked example.
AI Agents for Natural Language BI in Data and Analytics
This reference shows how an AI agent handles natural language BI tasks, from goal to decision, detailing the loop, tool usage, checks, and hand-off in data and analytics contexts.
AI Agents for Natural Language BI
This page defines the AI agent loop for natural language BI, lists required tools and data, and provides a concrete worked example from goal to decision.
AI Agents for Network Design in Supply Chain
A practical reference showing how an AI agent plans, calls tools, checks results, and stops for network design in supply chains, with a concrete worked example.
AI Agents for Network Design
A practical reference showing how AI agents plan, call tools, check results, and finish in network design tasks 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.