"AI agent" sounds abstract until you see the actual work. Inside a workspace built for it, an agent does the things a capable assistant would, across every part of the operation, from a request you make in plain language. Here is what that looks like, area by area.
Finance
Raise this month's invoices from completed work and send them. Chase the overdue accounts with polite, escalating reminders. Reconcile incoming payments and flag the mismatches. Pull the quarter's numbers together for review. The books stay close to real time because the agent maintains them as it works.
Communications
Summarise the morning's inbox and surface only what needs a decision. Draft replies to the routine messages for a quick send. Turn the requests buried in email into tasks and follow-ups. The inbox stops being a queue you grind through.
Sales
Move a deal to the next stage and book the follow-up. Create a deal from an enquiry and assign it. Summarise every open opportunity and what is blocking it this week. The pipeline reflects reality instead of last week's intentions.
Operations
Show what is low on stock and draft the purchase orders to cover it. Reconcile counts across locations. Build next week's schedule around the confirmed jobs. The agent acts on what it finds, not just reports it.
People
Onboard a new hire: set up their record, request their accounts, book first-week training, and tell the team. Summarise this month's leave and clashes. Chase the certifications that expire soon.
Marketing
Draft and schedule a campaign to a segment built from your own data. Publish a landing page and add it to the menu. Turn the latest form responses into contacts and tasks.
The common thread
Every one of these is a plain-language request that the agent carries out across the workspace, within your permissions and budget. None of it requires you to open a screen. See more by audience, by function, or as step-by-step guides.