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 Pricing Strategy in Product Management
AI agents for pricing strategy in product management demonstrate goal-driven pricing loops, integrating data, analytics, and tools to propose, test, and adjust price points with human oversight.
AI Agents for Pricing Strategy
This page shows how AI agents pursue pricing goals, plan actions, call tools, verify results, and hand off when needed, with a concrete worked example and governance to keep humans informed.
AI Agents for Prior Authorization in Healthcare
This page defines the AI agent loop for prior authorization in healthcare, listing required tools, data interfaces, and control points, with a concrete worked example showing end-to-end operation.
AI Agents for Prior Authorization
AI agents for prior authorization demonstrate goal-driven workflows that plan, query payer tools, interpret medical data, and hand off when required.
AI Agents for Privacy and GDPR Requests in Legal and Compliance
This page shows how an AI agent handles privacy and GDPR requests in legal and compliance, detailing the goal-driven loop, required tools, and a concrete worked example.
AI Agents for Privacy and GDPR Requests
Shows what an AI agent can do for privacy and GDPR requests, how the agent runs, and a concrete worked example from goal to finish.
AI Agents for Private Equity and Venture Capital Companies
Shows how to deploy and scale a single AI agent in a private equity or venture capital firm, including ownership, permissions, and trust-based scope expansion.
AI Agents for Private Equity and Venture Capital
Shows how an AI agent handles private equity and venture capital tasks, from goal to finish, with a concrete worked example of a single run.
AI Agents for Process Mining in Operations
Shows how a goal driven AI agent runs for process mining in operations, including planning, tool calls, checks, and handoff with a concrete worked example.
AI Agents for Process Mining
A practical reference showing how AI agents execute process mining goals, plan steps, call tools, verify results, and hand off when finished, with a concrete worked example.
AI Agents for Process Optimization in Chemicals
A practical reference showing how AI agents optimize chemical process workflows, including goal-driven loops, tool use, checkpoints, and a concrete worked example for design, operation, and governance.
AI Agents for Process Optimization in Manufacturing
This page details how AI agents execute goal-driven optimization in manufacturing, including loop steps, required tools, and a concrete worked example from goal to finish.
AI Agents for Process Optimization
A practical reference showing how AI agents perform goal-driven process optimization tasks, including tool use, plan execution, result checks, and a concrete worked example from goal to completion.
AI Agents for Processing Plant Optimization in Mining and Metals
Shows how AI agents plan, execute, and conclude processing-plant optimization tasks in mining and metals with concrete tool use and decision points.
AI Agents for Processing Plant Optimization
AI agents for processing plant optimization show goal-driven loops, tool calls, and a concrete worked example of optimizing a batch refinery line and finishing with verified actions.
AI Agents for Procure-to-pay in Procurement
Shows how an AI agent executes a procure-to-pay workflow from goal to finish, with tool use, checks, handoffs, and a concrete worked example.
AI Agents for Procure-to-pay
This page shows how an AI agent for procure-to-pay operates, including goal driven loop, tools, and a concrete worked example from goal to finish.
AI Agents for Procurement Companies
This page shows how procurement firms deploy and scale an AI agent, who owns it, and how its scope grows with trust, all through a company-wide worked example.
AI Agents for Procurement in Government and Public Sector
30 words. A practical reference showing how goal-driven AI agents execute procurement tasks in government, including planning, tool use, checks, and hands-off points, with a concrete worked example and required safeguards.
AI Agents for Procurement in Mining and Metals
Shows how a goal-driven procurement AI agent operates in mining and metals, including planning, tool use, validation, and hand-off with a concrete worked example.
AI Agents for Procurement
AI agents for procurement demonstrate goal-driven loops that plan, call supplier tools, verify results, and hand off when criteria are met, with a concrete worked example.
AI Agents for Product Analytics in Software and SaaS
This page outlines how AI agents execute product analytics tasks in software and SaaS, detailing goal-driven loops, tool usage, and a concrete worked example from goal to finish.
AI Agents for Product Analytics
A practical reference showing how an AI agent analyzes product analytics data, plans actions, calls tools, validates results, and hands off when needed.
AI Agents for Product Catalog Management in E-commerce
A practical reference showing how an AI agent manages product catalogs in e-commerce, including goals, tool usage, loop control, and 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.