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 Recipe Development in Food and Beverage
A practical reference showing how AI agents drive recipe development, how they plan, call tools, evaluate results, and hand off when finished.
AI Agents for Recipe Development
This page explains how AI agents approach recipe development, including goal-driven planning, tool use, evaluation, and hand-off, with a concrete worked example.
AI Agents for Records Management in Government and Public Sector
This page defines a practical loop for AI agents handling records management in government and public sector, with a worked example of goal-driven action.
AI Agents for Records Management
This reference shows how goal-driven AI agents manage records, plan actions, call tools, verify results, and decide when to stop, with a concrete worked example for records management.
AI Agents for Recruiting in Human Resources
Shows how a goal-driven AI agent handles recruiting tasks, from goal receipt to action and hand-off, with a concrete worked example.
AI Agents for Recruiting
This page shows how AI agents manage recruiting tasks from goal to decision, including tool use, checks, and handoff in a concrete worked example.
AI Agents for Referral Management in Healthcare
AI agents for referral management in healthcare demonstrate goal-driven handling of referrals, clinician communication, and status tracking with auditable logs and decision points.
AI Agents for Referral Management
AI agents for referral management demonstrate a goal-driven loop that handles referral intake, triage, routing, and tracking across systems with auditable human handoffs.
AI Agents for Refinery Operations in Oil and Gas
Shows how an AI agent plans, calls refinery tools, analyzes results, and hands off when goals are met within refinery operations.
AI Agents for Refinery Operations
This page details goal-driven AI agents for refinery operations, showing the loop from goal to planning, tool use, result checks, and handoff with a concrete worked example.
AI Agents for Refund Processing in Travel and Airlines
This page demonstrates how a goal-driven refund agent in travel and airlines plans, calls tools, evaluates results, and hands off when needed, with a concrete worked example.
AI Agents for Refund Processing
This page shows how AI agents handle refund processing, including goal-driven loop, tool calls, checks, and a concrete worked example.
AI Agents for Refunds and Returns in Customer Service
A practical reference showing how AI agents handle refunds and returns in customer service, including goals, tools, loop steps, and a concrete worked example.
AI Agents for Refunds and Returns
This page defines the AI agent loop for refunds and returns, showing goals, tools, checks, and when to stop, with a concrete worked example.
AI Agents for Regulatory Change Tracking in Legal
AI agents for regulatory change tracking in legal illustrate goal-driven loops, tool use, and decision handoffs, with a concrete worked example and practical setup guidance for compliance teams.
AI Agents for Regulatory Change Tracking
A practical reference showing how an AI agent tracks regulatory changes, plans actions, calls data tools, and stops with human review when needed.
AI Agents for Regulatory Compliance in Chemicals
Shows how an AI agent handles regulatory compliance in chemicals, from goal to tool use to decision, with a concrete worked example and safe-by-design stopping rules.
AI Agents for Regulatory Compliance in Energy and Utilities
AI agents for regulatory compliance in energy and utilities demonstrate a goal-driven loop: define the rule goal, plan steps, call data tools, verify outcomes, and hand off to humans when needed.
AI Agents for Regulatory Compliance Monitoring in Legal and Compliance
This page shows how regulatory compliance monitoring agents operate in legal contexts, detailing the goal-driven loop, required tools, stopping conditions, and a concrete worked example from goal to finish.
AI Agents for Regulatory Compliance Monitoring
This page demonstrates how AI agents tackle regulatory compliance monitoring, detailing the goal-driven loop, required tools, decision points, and a concrete worked example from goal to hand-off.
AI Agents for Regulatory Compliance
A practical reference showing how an AI agent handles regulatory compliance work, including goals, tool use, and a worked example from goal to finish.
AI Agents for Regulatory Reporting in Banking
Shows how an AI agent handles end-to-end regulatory reporting tasks in banking, including goal setting, tool use, validation, and hand-off to humans when required.
AI Agents for Regulatory Reporting
This page shows how AI agents handle regulatory reporting tasks, including goal setting, planning, tool use, result checks, and handoff to humans when required.
AI Agents for Regulatory Submissions in Pharma and Life Sciences
Shows how an AI agent can plan, call regulatory tools, and verify outputs for pharma submissions, 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.