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 Expense Auditing in Finance
This page shows how an expense auditing AI agent operates from goal to action, including a concrete worked example and the tools, data, and checks involved.
AI Agents for Expense Auditing
This page shows how an AI agent audits expenses end to end, including goal planning, tool calls, result checks, and hand-off to a human reviewer when needed.
AI Agents for Experimentation Analysis in Product Management
This page shows how AI agents analyze experimentation results in product management, plan actions, use tools, check outputs, and hand off when needed, with a worked example.
AI Agents for Experimentation Analysis
This reference shows how an AI agent analyzes experimentation data, plans actions, uses tools, checks results, and hands off when goals are met, with a worked example for parameter experiments.
AI Agents for Exploration Data Analysis in Mining and Metals
This page outlines a practical AI agent loop for exploration data analysis in mining and metals, detailing goals, tools, checks, and a concrete worked example.
AI Agents for Exploration Data Analysis
Shows how an AI agent plans, calls tools, evaluates results, and completes an exploration data analysis task with a concrete worked example.
AI Agents for Export Control Compliance in Defense and Aerospace
A practical reference showing how export control compliance AI agents plan, execute, and verify tasks in defense and aerospace workflows.
AI Agents for Export Control Compliance
Shows how an AI agent pursues export control compliance goals, using data, rules, and tool calls to verify classifications, licenses, and end-use checks without fixed workflows.
AI Agents for Facilities Management Companies
A practical reference showing how a facilities management company deploys goal-driven AI agents, their ownership, permissions, and scope growth through trust, with a company-wide worked example.
AI Agents for Facilities Management in Operations
Shows how a goal-driven AI agent handles facilities management tasks, from goal to tool use to decision, with a concrete worked example.
AI Agents for Facilities Management
This page details how AI agents operate in facilities management, including goal-driven planning, tool use, result checks, and hand-offs, with a concrete worked example.
AI Agents for Facility Management in Real Estate
Demonstrates a goal-driven AI agent that plans, executes tools, checks results, and hands off in facility management tasks for real estate, with a concrete worked example.
AI Agents for Facility Management
Shows how goal-driven AI agents manage facility management tasks from goal to action, including planning, tool calls, results checks, and handoff with a concrete worked example.
AI Agents for Faculty Administration in Education
Reference page detailing how AI agents execute goal-driven tasks in faculty administration, including tool use, loops, and a concrete worked example.
AI Agents for Faculty Administration
This page defines how AI agents operate in faculty administration, detailing the goal-driven loop, required tools, safeguards, and a concrete worked example from goal to finish.
AI Agents for Farm Financial Planning in Agriculture
This page defines how AI agents perform farm financial planning tasks, from goal setting to tool calls and results checks, ending with a hand-off when appropriate.
AI Agents for Farm Financial Planning
This page shows how AI agents manage farm financial planning tasks, detailing the agent loop, required tools, and a concrete worked example from goal to decision.
AI Agents for Farm Supply Chain in Agriculture
This page shows how an AI agent plans, calls tools, checks results, and hands off in a farm supply chain context, with a concrete worked example.
AI Agents for Farm Supply Chain
A practical reference showing how AI agents manage farm supply chain tasks, from goal to hands-off finish, with a concrete worked example and clear decision points.
AI Agents for Fashion and Apparel Companies
Demonstrates a first deployed AI agent in a fashion company, outlining ownership, permissions, and trust-based scope expansion with a full worked example.
AI Agents for Fashion and Apparel
This page shows how AI agents for fashion and apparel operate, including goals, tool usage, and a concrete worked example from goal to finish.
AI Agents for Feature Prioritization in Product Management
This page demonstrates how AI agents prioritize features in product management by goal->plan->tool calls->results assessment->handoff, with a concrete worked example and clear stop criteria.
AI Agents for Feature Prioritization
This reference shows how an AI agent prioritizes features, detailing the goal loop, tool interactions, checks, and handoffs, plus a concrete worked example for feature work.
AI Agents for Feature Request Analysis in Software and SaaS
This page demonstrates how goal-driven AI agents analyze feature requests in software and SaaS, plan actions, call tools, and hand off when needed, 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.