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 Dashboard Creation in Data and Analytics
A practical reference showing how an AI agent designs dashboards in data and analytics, with the agent loop, required tools, and a concrete worked example.
AI Agents for Dashboard Creation
Shows how an AI agent builds a dashboard end to end, including goals, planning, tool calls, checks, and handoff to humans where needed.
AI Agents for Data and Analytics Companies
This page shows how a data and analytics company deploys an AI agent, its ownership, permissions, and gradual scope expansion through trust, with a company-wide worked example.
AI Agents for Data and Analytics
A practical reference showing goal-driven AI agents for data and analytics, how they run, and a concrete worked example from goal to completion.
AI Agents for Data Cataloging in Data and Analytics
This page defines the AI agent loop for data cataloging, detailing goals, tools, stopping criteria, and a concrete worked example.
AI Agents for Data Cataloging
Shows how an AI agent can plan, call data tools, validate results, and finalize or hand off when cataloging metadata and schemas in a data lake environment with explicit governance checks.
AI Agents for Data Governance in Data and Analytics
AI agents for data governance in data and analytics demonstrate goal-driven loops that plan, call tooling, verify outcomes, and decide to finish or hand off; the page shows roles, tools, and a concrete worked example.
AI Agents for Data Governance
This reference shows how data governance AI agents plan, execute, and verify data stewardship tasks with tool calls, decision checks, and defined handoffs.
AI Agents for Data Pipeline Automation in Data and Analytics
This page shows how AI agents automate data pipeline tasks, including planning, tool use, checks, and handoff, with a concrete worked example.
AI Agents for Data Pipeline Automation
This page shows how AI agents automate data pipeline tasks from goal to action, including planning, tool calls, validation, and handoffs, with a concrete worked example.
AI Agents for Data Quality Management in Data and Analytics
This page shows how AI agents perform data quality management tasks in data and analytics, detailing the goal-driven loop, required tools, and a concrete worked example of a data quality run.
AI Agents for Data Quality Management
This page shows how AI agents approach data quality management, detailing the agent loop, required tools, stopping criteria, and a concrete worked example from goal to finish.
AI Agents for Database Migration in Software Engineering
This page demonstrates how an AI agent plans, partitions, migrates, validates, and verifies a database migration, using schema maps, data diffs, and rollback tools to reach a consistent target state.
AI Agents for Database Migration
This page demonstrates how AI agents manage database migration tasks, outlining goals, tool calls, decision checks, and a concrete worked example from start to hand-off.
AI Agents for Deal Coaching in Sales
Shows how a goal-driven AI agent handles deal coaching tasks, including planning, tool use, result checks, and hand-off, with a concrete worked example.
AI Agents for Deal Coaching
This page details how a goal-driven AI agent coaches deals, planning actions, calling CRM tools, analyzing outcomes, and handing off when needed.
AI Agents for Deal Sourcing in Private Equity and Venture Capital
This page explains how AI agents run deal sourcing work in private equity and venture capital, showing goals, tools, and an end-to-end worked example.
AI Agents for Deal Sourcing in Real Estate
A practical reference showing how AI agents run deal-sourcing in real estate, including goals, tools, and a concrete worked example.
AI Agents for Deal Sourcing
This reference shows how AI agents run deal-sourcing tasks, how they plan, call tools, evaluate results, and hand off when finished, with a concrete worked example.
AI Agents for Dealer Operations in Automotive
Shows how AI agents plan, execute, and hand off tasks in automotive dealer operations, with a concrete worked example and clear stop criteria.
AI Agents for Dealer Operations
Show how AI agents operate in dealer operations, including planning, tool use, result checks, and handoffs, with a concrete worked example from goal to finish.
AI Agents for Defect Prediction in Manufacturing
A concise reference showing how an AI agent analyzes production data, plans defect checks, calls tools, and stops with a validated defect prediction decision.
AI Agents for Defect Prediction
This reference shows how a goal-driven AI agent handles defect prediction tasks, from goal to tool use, result checks, and hand-off, with a concrete worked example.
AI Agents for Defense and Aerospace Companies
This page shows how to deploy an AI agent inside a defense and aerospace company, covering ownership, permissions, scope growth, and a worked company-level 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.