Which back-office jobs can you hand to an AI agent?

AI agents for business operations can take over parts of the back-office work today, as long as a person checks the output that matters. The products read for this page document two pieces of it: a document service that extracts text, tables and typed fields for agents and applications to use, and a scheduling assistant that recommends meeting times from attendees' calendars. Neither is documented as running the office on its own. Microsoft's guidance for its document service says to "keep a human in the loop." So the job you hand over is "do the routine part and flag the rest", and the job you keep is "check the exceptions and own the decision".

"Operations" is a vague word, so this hub defines it narrowly. Here it means back-office work: documents, data entry, scheduling and internal requests. It does not cover IT operations (servers, incidents, deployments) or logistics (shipping, warehouses, fleets). Customer-facing support has its own section, and invoice processing sits under accounts payable.

What AI agents do in business operations today

Two products show what the building blocks of operations work do and where the limits are written down. Each is described from its own documentation as of November 2026; we have not tested either. No documentation read for this page describes an agent handling internal requests from staff, so that part of operations has no product evidence here.

• Reading documents. According to Microsoft's documentation, Azure Document Intelligence, a document-processing service that prepares data for agents and applications, extracts printed and handwritten text, tables and document structure, and offers prebuilt models for document types such as invoices, receipts, bank statements, contracts, pay stubs and US tax forms. Custom models are trained on your labeled documents, and a custom classifier can identify the document type before extraction. Fields come back as typed values, such as a date or a currency amount.
• Scheduling. Microsoft's support page for Copilot in Outlook says that when you type a request such as a 30-minute meeting about a report, Copilot "will check the calendars of all the attendees and recommend a mutually convenient time to meet."

Where the documentation draws the line. Microsoft's transparency note for Document Intelligence is the most explicit limits document found for this page. It says "machine learning models aren't perfect" and that a human should review output in high-stakes scenarios (for example, ones affecting someone's consequential rights) or with sensitive data. The service returns a confidence value between 0 and 1 for each extracted word and key-value mapping. The note says customers should run a pilot on their own documents, then may estimate a confidence threshold. Its example sends results with confidence greater than or equal to 0.80 to straight-through processing and applies human review below 0.80. It also warns that the service "was not designed or evaluated for the award or denial of benefits," naming medical insurance and loan approvals.

The note also explains why a document can be wrong even when almost every word is right. In Microsoft's example, 2 wrong words out of 30 is a 6% word error rate, but if those words sit in 2 of 10 names, 20% of the names are wrong. One character wrong in the paid amount might cause the whole invoice or receipt to be flagged as incorrect. The note says measuring both word error rate and entity error rate is useful.

Jobs you can hire an agent for

Each job has its own page with a task breakdown, a brief template you can copy, risks and how to run a trial.

• JobSupervised
  AI agent for document processing and extraction

  An AI agent can sort incoming documents, split bundled PDFs and extract the fields you define into structured data. Low-confidence fields and any decision that acts on the data stay with a person.
• JobSupervised
  AI agent for data entry: what it does, what you check

  An AI agent can read emails, forms and documents and enter the data into business systems through their screens, even without an API. A person sets the field rules, answers the exceptions it escalates and samples records against the source.

Ready

0of 2

Supervised

2of 2

• AI agent for document processing and extraction
• AI agent for data entry: what it does, what you check

Assist only

0of 2

Not yet

0of 2

They differ in what the agent reads and what a mistake costs:

Job	What the agent does	What a person keeps
Document processing	Classifies incoming documents and extracts text, tables and fields, with a confidence value for each extracted word and key-value mapping (as documented for Azure Document Intelligence)	Reviewing low-confidence results and documents of unknown type; human review in high-stakes scenarios affecting someone's consequential rights or with sensitive data; no use for award or denial of benefits, including medical insurance and loan approvals
Data entry	Extracted key-value pairs can be entered into a database or CRM through robotic process automation (per Microsoft's transparency note)	Spot-checking entries against the source, fixing rejects, owning the system of record

If the documents are supplier invoices, start with accounts payable instead, which covers approval and payment controls. For sorting incoming customer requests, see ticket triage.

Roles they affect

This function covers one role so far. Its page goes task by task through what an agent can take and what stays with the assistant.

• Role
  Can AI replace administrative assistants? Task by task

  Microsoft and Google document AI features that draft email, suggest meeting times, assign a priority to incoming mail and write meeting notes. Review before sending is documented for Copilot's email draft and for Gmail's suggested times; Gmail's Help me write only generates or refines a draft, and Copilot's scheduling page recommends a time and does not describe a review.

For scale: the U.S. Bureau of Labor Statistics puts the median annual wage for secretaries and administrative assistants at $48,310 (May 2025), with about 3.5 million jobs in 2025. Their BLS duty list includes scheduling appointments, arranging staff meetings, preparing memos, invoices or reports, and maintaining databases and filing systems. BLS projects employment to decline 2% from 2025 to 2035 and says technology, including AI systems and digital tools, enables staff in many organizations to "prepare their own documents without the help of secretaries."

General office clerks, whose BLS duties include collecting information, performing data entry, and copying, filing and updating documents, had a median wage of $21.64 an hour in May 2025 and about 2.6 million jobs. BLS projects their employment to decline 6% from 2025 to 2035, citing "technology that automates document preparation and other clerical tasks."

The BLS duties closest to what the products above document are scheduling, data entry and filing. Answering phones, receiving visitors, negotiating with vendors and making decisions on a manager's behalf are not covered by any documentation read for this page.

Where to start

Start with work where an error is cheap to catch before it takes effect: extracting fields from a document type you see often, or entering data into a system someone already reviews. Avoid starting with anything that pays money, decides about a person's benefits or loan, or sends something outside the company without review.

For example (assume, for this example, an office of 20 people that receives about 200 signed customer order forms a month by email): you ask an agent to extract the customer name, order date, product codes and total from each form into a spreadsheet. Fields with a confidence value below the threshold you set in a pilot are highlighted. A person checks every highlighted field against the form, and samples 10 unhighlighted forms a week. The share of sampled forms with an error tells you whether to raise or lower the threshold.

Before you hand over any operations job, we recommend:

1. Write the brief down. Name the documents or requests, the fields or answers you need, where the output goes and what counts as an error. The hiring guide walks through it.
2. Test on your own documents. Microsoft tells customers to "conduct their own evaluations" because performance "will vary depending on the real-world solutions for which it's implemented." A vendor demo on clean samples tells you little about your scans. The trial guide shows how to set one up.
3. Route by confidence. Decide which results go through automatically and which go to a person, and write the threshold down.
4. Measure the fields you use. Our recommendation: alongside word errors, count wrong names, amounts and dates, since those are what break a record.
5. Know what data the agent touches. Document work can involve personal data such as IDs and pay stubs. Microsoft's note says privacy managers should consider retention policies for the extracted text and values and for the underlying documents or images. Ask counsel which privacy obligations apply to your documents and jurisdiction.
6. Keep a person on the exceptions. The guide on supervising an agent covers review cadence and handover.

If you have a back-office job in mind, describe it below.

Sources

1. 1
   What is Azure Document Intelligence in Foundry Tools?

   Microsoft LearnPrimaryAccessed Nov 14, 2026

2. 2
   Transparency note for Document Intelligence

   Microsoft LearnPrimaryAccessed Nov 14, 2026

3. 3
   Schedule a meeting using Copilot

   Microsoft SupportPrimaryAccessed Nov 14, 2026

4. 4
   Secretaries and Administrative Assistants: Occupational Outlook Handbook

   U.S. Bureau of Labor StatisticsPrimaryAccessed Nov 14, 2026

5. 5
   General Office Clerks: Occupational Outlook Handbook

   U.S. Bureau of Labor StatisticsPrimaryAccessed Nov 14, 2026