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 Cleaning Operations
This page shows how AI agents execute cleaning operations, from goal to finish, including required tools, decision points, and a concrete worked example with precise steps and audits.
AI Agents for Client Onboarding in Accounting and Tax
Shows how an AI agent autonomously handles client onboarding in accounting and tax, detailing the goal-loop, tools, checks, and a concrete worked example.
AI Agents for Client Onboarding in Professional Services
This reference shows how a goal-driven AI agent handles client onboarding tasks, tool use, checks, and hand-offs, with a concrete worked example that scales with governance and audit requirements.
AI Agents for Client Onboarding
Shows how an AI agent can handle client onboarding goals, plan steps, call tools, verify results, and hand off for review with a concrete worked example.
AI Agents for Client Reporting in Capital Markets
A practical reference showing how AI agents handle client reporting in capital markets, from goal to tool use, checks, and hand-off, with a concrete worked example.
AI Agents for Client Reporting in IT Services and MSP
This page details how AI agents perform client reporting in IT services and MSPs, outlining goals, tool usage, and decision checkpoints, plus a concrete worked example.
AI Agents for Client Reporting in Professional Services
This page demonstrates how AI agents autonomously assemble client-facing reports, verify data, and deliverables in professional services while preserving auditability and control.
AI Agents for Client Reporting
A practical reference showing how AI agents drive client reporting, including goals, tool calls, result checks, and a worked example from goal to delivery.
AI Agents for Climate Risk Analysis in ESG and Sustainability
A practical reference showing how climate risk analysis AI agents operate in ESG and sustainability, including goal-driven loops, tool use, checks, and a worked example.
AI Agents for Climate Risk Analysis
A concise reference showing how AI agents run end to end in climate risk analysis, including tool use, decision points, and a concrete worked example from goal to finish.
AI Agents for Clinical Decision Support in Hospitals
Shows how an AI agent implements clinical decision support in hospitals, detailing the loop from goal to tool use, checks, and hand-off with a worked example as reference.
AI Agents for Clinical Decision Support
AI agents for clinical decision support demonstrate goal-driven reasoning: goal formation, planning, tool calls, result checks, and handoffs in a concrete worked example within a clinical data context.
AI Agents for Clinical Documentation in Healthcare
A practical reference showing how AI agents run in clinical documentation, including goals, tools, loops, and a concrete worked example.
AI Agents for Clinical Documentation
This page shows how AI agents can create, verify, and finalize clinical documentation by planning, calling tools, and handing off when human review is needed.
AI Agents for Clinical Trial Matching in Healthcare
Shows how an AI agent can autonomously identify eligible patients and match them to trials, using data mapping, eligibility logic, and audit trails.
AI Agents for Clinical Trial Matching
A practical reference showing how AI agents perform clinical trial matching, from goal to action, with a concrete worked example and required tooling, data, and governance.
AI Agents for Clinical Trial Operations in Pharma and Life Sciences
This page defines how AI agents operate in clinical trial operations, detailing goals, tool use, stop criteria, and a concrete worked example.
AI Agents for Clinical Trial Operations
Shows how an AI agent can run a clinical trial operation loop with concrete steps, tools, and a worked example from goal to finish.
AI Agents for Cloud Cost Optimization in IT Operations
This reference shows how goal-driven AI agents optimize cloud spend in IT operations, detailing the loop, tools, decision checkpoints, and a concrete worked example for guidance.
AI Agents for Cloud Cost Optimization
Shows how an AI agent plans, calls cloud tools, and stops, with a worked example for cloud cost optimization.
AI Agents for Cloud Security Posture in Cybersecurity
This page defines a goal-driven AI agent loop for cloud security posture management, including tools, checks, handoffs, and a concrete worked example.
AI Agents for Cloud Security Posture
This page documents the goal-driven loop for AI agents managing cloud security posture, tools, checks, handoffs, and a concrete worked example from goal to finish.
AI Agents for Code Generation in Software Engineering
AI agents for code generation in software engineering demonstrate goal-driven planning, tool orchestration, and validation, showing how an agent proposes changes, calls code gen tools, tests, and hands off when done.
AI Agents for Code Generation
30-word summary: This reference shows how AI agents handle code generation tasks, detailing the goal-driven loop, required tools, stopping criteria, and a concrete worked example to guide implementation and evaluation.
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.