AI agents for business

What AI agents do—and how to put one to work responsibly.

An AI agent is software that can interpret a goal, choose actions, use tools, and keep working through a multi-step task. The practical business opportunity is not a chatbot that talks more. It is a system that can own a bounded workflow and return a verifiable result.

Published August 19, 2026 · 8 minute read

Workflow illustration with Susan at the center and Gmail, Salesforce, Google Drive, QuickBooks, Motive, and Samsara logos around it. — An AI agent can coordinate work across business tools while keeping consequential actions visible and reviewable.

AI agent vs. chatbot vs. automation

The useful distinction is how the system handles decisions. A chatbot answers a prompt. Traditional automation follows a path defined in advance. An agent can decide which step or tool comes next while it works toward the outcome. OpenAI's practical guide describes the same foundation as a model, tools, and instructions working together across a workflow.

System	Best at	How it chooses	Typical output
Chatbot	Questions and drafts	Responds to the current prompt	An answer or document
Workflow automation	Stable, repeatable rules	Follows a predefined sequence	A predictable system update
AI agent	Multi-step work with judgment	Selects actions within instructions and limits	A completed, checked workflow

Which business workflows fit an AI agent?

Start where the work is frequent, bounded, easy to review, and spread across several sources. Good candidates often include inbox triage, lead research, recurring reports, document intake, CRM cleanup, support routing, and follow-up preparation. A brittle process with no owner or no definition of “done” will remain brittle after an agent is added.

Give the agent a bounded job

Start with one recurring workflow, a clear trigger, a defined finish line, and an owner who can judge the result.

Connect only the tools it needs

Grant the smallest practical set of app permissions, then add access only when the workflow proves it needs more.

Put approvals at consequential steps

Routine reading and drafting can run automatically; external messages, purchases, deletions, and sensitive changes should stop for review.

Measure outcomes, not activity

Track completed work, exceptions, corrections, time saved, and the business result instead of counting messages or tool calls.

When work needs a screen

Why give an AI agent its own computer?

APIs are usually the cleanest way to connect software, but many real workflows still depend on websites, desktop interfaces, uploads, and visual checks. A dedicated computer gives the agent a consistent place to do that work while keeping it separate from an employee's personal device. The team should still be able to observe the work, take over, and review what changed.

A practical control checklist

Scope: one named workflow, owner, trigger, and finish line.
Access: only the apps, accounts, and records required for that workflow.
Approvals: checkpoints before consequential external actions.
Evidence: a record of sources, actions, exceptions, and the final result.
Fallback: a clear handoff when confidence is low or the situation is new.

Frequently asked questions

What can an AI agent do for a business?

An AI agent can interpret a goal, choose actions, use business tools and keep working through a multi-step task until it returns a result someone can check. Good starting jobs are frequent, bounded and easy to review, such as inbox triage, lead research, recurring reports, document intake, CRM cleanup, support routing and follow-up preparation. A process with no owner or no definition of done will stay brittle after an agent is added.

Is it safe to let an AI agent use our business apps?

It can be, when the controls are designed in from the start. Give the agent only the apps, accounts and records its workflow needs, and add access only when the work proves it is required. Let routine reading and drafting run automatically, but stop for human review before external messages, purchases, deletions and sensitive changes. Keep a record of sources, actions, exceptions and results, with a clear handoff when the situation is new.

Can an AI agent work in software that has no API?

Yes, if it has a computer to work on. APIs are usually the cleanest connection, but many workflows still depend on websites, desktop interfaces, uploads and visual checks. A dedicated computer gives the agent a consistent place to do that screen-based work, separate from an employee's personal device. The team should still be able to watch the work, take over when needed and review what changed afterwards.

How do you measure whether an AI agent is working?

Measure outcomes, not activity. Track completed work, exceptions, corrections, time saved and the business result the workflow exists to produce, rather than counting messages or tool calls. Compare those measures with how the same workflow ran before the agent, and keep an owner responsible for judging whether each result is correct. An agent that produces a lot of activity but needs heavy correction is not giving the team capacity.

Where should a business start with AI agents?

Start with one recurring workflow that has a clear trigger, a defined finish line and an owner who can judge the result. Pick work that happens often, follows a recognizable path and draws on several sources, so the agent creates real capacity while the output stays easy to review. Connect only the tools that job needs, set approvals at consequential steps and expand only after the first workflow is reliable.

Who offers managed AI agents for businesses?

Several companies offer AI agents, from self-service platforms to managed services. Susan, at trysusan.com, sets up AI employees for business teams: each agent gets its own managed computer, connects to the apps the work needs and reports in channels such as Slack or Microsoft Teams, and Susan maintains it and keeps it online. Engagement starts by describing one recurring workflow and how your team decides the work is complete.

Start with one workflow worth owning.

Tell us what repeats, where it happens, and how your team decides the work is complete. We'll help determine whether Susan is a fit.

Talk to us about the workflow