What an AI Employee Is
We use the term "AI employee" for an AI that has a name, a role, and a field of expertise, that works together with other AIs to carry out business, and that works much like a human being.
This article explains it on the basis of the form GIZIN actually operates.
We at GIZIN have kept this running for a year, and as of July 2026 we have given names and specialized roles to 45 AI employees. Across several departments — article editing, development, accounting, customer support — we will show you in the middle of this article, together with actual numbers and actual failures, what they could and could not do.
First: how does an AI employee differ from the AI that many people are already using?
How AI Employees Differ from ChatGPT, AI Agents, and RPA
These four are not mutually exclusive product categories; they are ways of using AI for different purposes.
ChatGPT is a form of using conversational AI, an AI agent is a mechanism that executes toward a goal, RPA is the automation of predetermined operations, and an AI employee is a design for roles and continuous operation.
What separates an AI employee from the other three lies in the design behind two questions: whose job is this, and how far do you keep it going?
| Main entry point | Memory and continuity | Range of action | Where the human judges | |
|---|---|---|---|---|
| Conversational AI such as ChatGPT | A chat screen | Refers to past information as well, depending on settings | Answering and generating. External operations depending on the feature | The person using it judges each time |
| AI agent | An instruction stating a goal | Depends on the design | Chooses and executes steps in order to reach the goal | Needs a design that places checks before and after execution |
| RPA | Registration of a business flow | Holds the steps fixed | Moves exactly as the registered operations specify | A person handles exceptions |
| AI employee | Assignment of a role and duties | Carries over across duties and across the people in charge | Works and coordinates within the range of the role | Approval and checking are built into the process |
What They Can Do
For each of the five areas of work GIZIN has put this into practice in, here are the tasks we delegate, the judgments we keep with humans, and an actual example from GIZIN's operation.
| Area of work | Tasks delegated | Judgments kept by humans | Example at GIZIN |
|---|---|---|---|
| Customer support | First-line answers to FAQs, first-line response outside business hours | Exception handling, decisions on apologies and compensation | Replied to all 16 store reviews, in both Japanese and English |
| Internal help desk and secretarial work | Compiling daily reports, sorting email, scheduling | The final decision on priority | Sorted 100 sales emails a month down to the 3 worth reading |
| Accounting and back office | Matching invoices, checking expenses, month-end closing work | Accounting policy, tax judgments | Month-end closing went from 3 days to 1 hour |
| Web and development | Implementation, fixes, drafts of tests | Whether to deploy to production, decisions on design | AI employees handle all of the update work |
| PR and content | Draft social posts, drafts, first drafts of articles | Whether to publish, final responsibility for fact-checking | Presentation materials, press releases |
They produce as widely as a human and in as much volume as a machine, but that does not mean the human role disappears. Deciding the purpose, granting authority, making the final call, carrying responsibility toward the outside world — the roles humans carry become fewer, but the important ones remain.
Running 45 of Them for a Year: What Worked and What Did Not
A year ago we began transforming into a company run with AI employees at its center — article editing, development, accounting, customer support, PR.
What the Numbers Confirmed
Replies to store reviews. Reviews arriving on the app stores used to pile up unanswered. Once we placed an AI employee in charge, all 16 were answered on the first day of employment, in both Japanese and English. Inquiries arriving in the middle of the night now get a first reply as well.
Sorting sales email. People used to open and sift through the roughly 100 sales emails arriving each month. Now an AI employee sorts them, and what a person looks at is about 3 a month.
Month-end closing. Month-end closing work that used to take 3 days now finishes in 1 hour. Journal entries into the accounting software are all done by AI employees as well.
Of course, simply bringing in AI employees does not produce change by itself. It is the result of deciding the range to delegate, placing someone to check, and fixing the procedure every time something failed.
What They Could Not Do
Over a year of operation, there were things we delegated that did not work out.
- Presenting an unverified value as an established fact. We had a failure where a number displayed on screen was placed, as it was, at the head of a one-year review. The number was not wrong; what had disappeared partway through the report was the state of "not yet confirmed."
- Mistaking the state of things. Treating a service whose name has already changed as the same thing, going by the old wording. Or believing a process that has already finished is still under way. Where a human would catch on — "wait, didn't this change?" — it passes straight through.
- Material for a decision not reaching the person who acts. Correct information was correctly compiled, and then sent up to someone other than the person who would actually act on it. However correct the content, work does not move if it arrives at the wrong place.
What This One Year Taught Us
What made the difference between success and failure with AI employees, we found, was whether — after delegating to the AI — we had gone as far as designing checks, records, and who holds responsibility. By classifying failures as they occur and reflecting them into procedure, what kinds of failures there are and how they were fixed accumulates.
What It Costs (Actual Figures)
If you are only starting with 2 or 3 AI employees, you do not need a dedicated machine. The computer you already have, one contract for a personal paid AI plan, and you can start from a few thousand yen a month.
Delegating one simple routine task to one AI employee. For that alone, you need no high-performance GPU, no locally run AI, and no contracts with multiple vendors.
Costs rise not with the number of people as such, but when the following conditions are added.
- Running several AI employees at the same time
- The kinds of work increase
- Work with high confidentiality increases
- Using image or video generation
For reference, in our case the main AI contracts come to roughly 100,000 yen a month, and we use a Mac Studio for running things locally. We started with a single MacBook, but as we increased the number of people and the range of uses, we ended up with a two-machine setup: 40 people doing regular work on the Studio, and 5 doing R&D on the MacBook.
→ See how AI employees are introduced and what they cost, in detail
Risks and Countermeasures
Risks are easier to organize if you think of them in the following four groups.
| Group | What happens | The first countermeasure to put in place | Judgment kept by humans |
|---|---|---|---|
| Information | Confidential or personal information passes to an unintended place | Decide, for each duty, the range of information that may be entered | Selection of contracts and environments |
| Quality | Incorrect content, or values that have not been checked, get mixed into deliverables | Decide who checks, and the conditions for stopping | Whether to publish or submit |
| Authority and external actions | Operations that are hard to undo — sending, publishing, payment — get executed | Narrow execution authority, and place approval in the process | The approval itself |
| Legal | Something goes outside without meeting the requirements for rights or disclosure | Decide the flow for checking documents that go outside | The final legal judgment |
As for authority, rather than handing over all of it from the start, it is realistic to widen it in this order: read-only, then up to drafts, then execution with approval attached. We too limit the authority to deploy to production to a small number of people.
And even when we call them AI employees, responsibility toward the outside world and the final judgment remain with humans. Legal judgments, and what structure is appropriate, differ by each company's local rules and by workflow.
Frequently Asked Questions
Q. Do AI employees replace human employees? Our operation is not premised on replacing human employees. Deciding the purpose, the final judgment, and responsibility toward the outside world are carried by humans. We pair the division of roles with checking, and decide the range to delegate on that basis.
Q. Can I start with one? You can. In fact we recommend starting with one. Delegating one narrow task, stabilizing it while checking, and only then adding the next — that order fails less often.
Q. What does it cost? For 2 or 3, you can start from a few thousand yen a month with a computer you already have and one paid AI plan contract. A dedicated machine is not necessary. For details, see the section "What It Costs."
Q. What is the difference from ChatGPT? The biggest difference is whether you begin having designed roles, memory, and continuous operation. An AI employee is useful when you want to delegate one duty over a long period.
Q. Can they handle confidential information? It depends on the environment, the contract, the authority, and the rules for input. Start by deciding what may be entered in this particular duty.
Q. Can I start without specialist knowledge? You can start small. But the work of putting into words the tasks to delegate and the criteria for checking is necessary. What is asked for here is less technical knowledge than the ability to break work down.
Q. Should I build it myself or use implementation support? We recommend this order: first build one person, one duty yourself, and consider support at the point where you find role design and checking difficult. The concrete method is explained in How to Create AI Employees.