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 Dispute Resolution
A practical reference showing how dispute-resolution AI agents plan, execute tools, verify results, and hand off when needed.
AI Agents for Distributor Management in CPG
This page shows how an AI agent handles distributor management tasks in CPG, detailing the loop, tools, and a concrete worked example from goal to finish.
AI Agents for Distributor Management
This page demonstrates how an AI agent can manage distributor relationships, plan actions, call tools, verify results, and hand off when needed, with a concrete worked example.
AI Agents for Dock Scheduling in Logistics
This page shows how an AI agent schedules docking windows, coordinates resources, and adapts to delays in a logistics hub with a concrete worked example.
AI Agents for Dock Scheduling
This reference defines how an AI agent plans dock scheduling tasks, calls tools, evaluates outcomes, and hands off when needed, with a worked example for visibility and reuse in systems.
AI Agents for Document Control in Construction
A practical reference showing how AI agents manage construction document control tasks, run the loop, and deliver a concrete worked example for field teams and office staff.
AI Agents for Document Control
AI agents for document control demonstrate goal-driven work: planning, tool use, result checks, and hand-off in a controlled loop with a concrete worked example.
AI Agents for Documentation Generation in Software Engineering
A practical reference showing how AI agents generate software project documentation, run the loop from goal to tool use, and produce a concrete worked example.
AI Agents for Documentation Generation
AI agents for documentation generation demonstrate a goal-driven loop that creates, updates, and validates docs with source access, templates, and publishing checks, showing how to plan, call tools, and hand off when finished.
AI Agents for Donor Communication in Nonprofits
A practical reference showing how AI agents handle donor communication tasks, run the agent loop, and deliver a concrete worked example in nonprofit fundraising context.
AI Agents for Donor Communication
This page defines how an AI agent handles donor communication tasks with goal-driven planning, tools, result checks, and a concrete worked example demonstrating end-to-end operation.
AI Agents for Donor Management in Nonprofits
This page shows how a goal-driven AI agent handles donor management tasks, from data gathering to outreach and reporting, with a concrete worked example.
AI Agents for Donor Management
Demonstrates a goal-driven AI agent loop for donor management, with tools, data flows, and a concrete worked example.
AI Agents for Drilling Optimization in Oil and Gas
This reference shows how AI agents for drilling optimization in oil and gas operate, including goal-driven loops, tool calls, result checks, and handoffs, plus a detailed worked example of a complete run.
AI Agents for Drilling Optimization
This page outlines the AI agent loop for drilling optimization, detailing goals, tools, and a concrete worked example from goal to finish.
AI Agents for Driver Management in Transportation and Mobility
This page explains how an AI agent manages driver schedules, compliance, and routing in transportation, including the run loop and a concrete worked example for reference.
AI Agents for Driver Management
This page shows how an AI agent manages driver scheduling, routing, and duties through goal-driven planning, tool calls, and result checks, with a concrete worked example that demonstrates end-to-end execution and governance.
AI Agents for Drug Discovery in Pharma and Life Sciences
Shows how a drug discovery AI agent plans, calls tools, evaluates results, and hands off, with a worked example from goal to finish.
AI Agents for Drug Discovery
Shows how an autonomous agent plans, calls cheminformatics tools, analyzes results, and iterates to advance a drug discovery project.
AI Agents for Due Diligence in Capital Markets
This page shows how a goal-driven AI agent performs due diligence in capital markets, including planning, tool use, checks, and handoff, with a concrete worked example.
AI Agents for Due Diligence in Corporate Strategy
Shows how an AI agent conducts due diligence in corporate strategy, including goal planning, tool calls, result checks, and hand-off with a concrete worked example.
AI Agents for Due Diligence in Legal
AI agents for due diligence in legal demonstrate a goal-driven loop: define a compliance goal, plan steps, invoke tools, verify results, and escalate for review when needed.
AI Agents for Due Diligence in Private Equity and Venture Capital
Shows how AI agents perform due diligence in private equity and venture capital, outlining goals, tool use, loop flow, and a concrete worked example from start to finish.
AI Agents for Due Diligence in Real Estate
This page shows how an AI agent performs due diligence in real estate, from goal to tool use, checks, and handoff, 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.