59 AI Employee Ideas You Can Build for Your Business

The London Tube map lies about London.

Stations that are miles apart look like polite neighbors. Curving routes become tidy lines. Geography is bent until the connections make sense.

That was the point. In 1933, electrical draughtsman Harry Beck replaced geographic accuracy with a diagram inspired by the circuit drawings he made at work. Transport for London says the first version was considered too radical, then a trial showed that passengers preferred the clearer network. Beck did not help people by drawing every alley. He helped them see where to get on, where to change, and where they would end up. Transport for London tells the story here.

Harry Beck's original 1933 Tube map, shown for reference. Image source: Transport for London.

Most conversations about AI employees need the same correction.

People ask, "Which AI should I hire?" as if Claude, ChatGPT, Gemini, or another model will arrive wearing a little tie and request a dental plan. The model is not the job. It is part of the machinery.

The useful map shows:

• what signal starts the work;
• what facts the employee receives;
• what judgment it is allowed to apply;
• which tools it can use;
• where a person approves the work;
• what checked result comes out;
• which job receives that result next.

That is the map below. It contains all 59 jobs from the Sevedge Builds Big Picture, plus the technology stacks that can give those jobs eyes, memory, hands, and a place to work.

Do not build all 59. London did not dig the entire Underground because one person needed to get to Paddington.

Choose one useful route. Make it run. Then add the next station.

An AI employee is a job system, not a personality

Giving an AI a name can be fun. Giving it a finish line is more useful.

A dependable AI employee has eight parts:

The model can change. The job should remain legible.

If your employee depends on one heroic prompt containing the process, the passwords, last month's exceptions, seven pasted spreadsheets, and a stern paragraph about not making mistakes, you do not have an employee. You have a very anxious piñata.

The complete 59-job AI employee atlas

These are example seats, not a shopping list. Each one can begin as a narrow assistant that researches or drafts. Access and automation can expand after the output earns trust.

1. Executive Office: turn direction into decisions

1. AI Integrator / CEO: Converts the owner's direction into a ranked company plan, reconciles conflicts between departments, and returns the few decisions that need human judgment.
2. Chief of Staff: Builds the operating rhythm: meeting briefs, weekly scorecards, issue lists, decision logs, and follow-through across leaders.
3. Founder's Executive Assistant: Organizes inbox, calendar, tasks, waiting-for items, and daily priorities using Getting Things Done principles and other productivity methods.
4. Executive Briefing Analyst: Combines calendar, CRM, project, financial, and market context into a short pre-meeting or morning brief.
5. Leadership Scorecard Analyst: Collects department metrics, checks definitions, flags exceptions, and produces one leadership scorecard with source links.
6. Issues and Decisions Coordinator: Captures unresolved issues, gathers the relevant evidence, records decisions, and tracks the owner and due date of each next step.

2. Revenue Office: keep one commercial plan

7. Chief Revenue Officer: Coordinates sales, marketing, and paid media around one revenue target, one set of definitions, and the constraints that could block the plan.
8. Revenue Research Analyst: Studies customers, competitors, market shifts, pricing, and channel performance so revenue decisions begin with evidence.
9. Revenue Operations Analyst: Keeps lifecycle stages, lead routing, attribution, handoffs, and revenue reporting consistent across systems.
10. Revenue QA Auditor: Tests whether pipeline, marketing, and advertising reports agree, then traces mismatches back to missing or misclassified records.

3. Sales: move the right opportunities forward

11. VP of Sales: Reviews pipeline health, coaching needs, forecast risk, and rep priorities, then turns them into a focused sales plan.
12. Sales Research Analyst: Prepares account, industry, contact, and timing research with citations before outreach or a sales call.
13. Lead Intelligence Specialist: Enriches new leads, detects duplicates, scores fit and intent, and routes each opportunity to the right owner.
14. Sales Analyst: Reviews calls, emails, estimates, objections, and outcomes to recommend the next action for each active opportunity.
15. Follow-Up Specialist: Drafts and schedules useful follow-ups, remembers the conversation, and stops or changes course when the lead replies.
16. Pipeline Manager: Finds stale deals, missing next steps, weak dates, and stage errors, then requests or applies the approved CRM update.
17. Sales QA Auditor: Checks research, personalization, promises, pricing, consent, and CRM accuracy before or after customer-facing work.

4. Marketing: turn customer evidence into demand

18. VP of Marketing: Chooses the audience, positioning, campaign priorities, channel mix, and measures that support the revenue plan.
19. Market Research Analyst: Tracks category changes, competitors, search behavior, offers, and customer alternatives using source-backed research.
20. Customer Voice Researcher: Mines calls, reviews, surveys, chats, and win-loss notes for the exact language customers use about problems and outcomes.
21. Content Strategist: Converts business goals and customer evidence into themes, briefs, formats, channels, and a publishing calendar.
22. Content Production Specialist: Produces drafts, clips, graphics, emails, and repurposed variations from an approved brief and source material.
23. SEO Specialist: Finds search opportunities, maps intent, improves pages, checks technical issues, and measures whether useful pages earn qualified discovery.
24. Marketing QA Auditor: Verifies claims, links, brand voice, accessibility, tracking, offer details, and channel requirements before publication.

5. Paid Media: buy attention without hiding the numbers

25. VP of Paid Media: Sets channel roles, budget boundaries, testing priorities, and the business outcomes that decide where money moves.
26. Paid Media Research Analyst: Studies demand, keywords, audiences, competitors, placements, and platform changes before a campaign is built.
27. Media Buyer: Builds campaign drafts, audiences, keywords, bids, budgets, and placements, then publishes only after the required approval.
28. Creative Testing Strategist: Turns customer evidence into testable hooks, angles, formats, and hypotheses instead of requesting "more creatives" from the universe.
29. Landing Page Analyst: Compares ad promise, page message, behavior, speed, form completion, and conversion quality to find where intent is lost.
30. Attribution Analyst: Joins ad, web, call, CRM, and revenue data to explain which campaigns created qualified business, not merely inexpensive clicks.
31. Paid Media QA Auditor: Checks budgets, geography, exclusions, URLs, tracking, conversion events, naming, creative, and approval status before launch.

6. Operations: match promises to capacity

32. Chief Operating Officer: Converts demand into a delivery plan, resolves cross-team constraints, and returns the exceptions that require leadership action.
33. Operations Research Analyst: Pulls order, project, staffing, inventory, vendor, and service data into an evidence-backed operations brief.
34. Workflow Architect: Maps the current handoffs, removes needless steps, defines triggers and exception paths, and designs the future workflow.
35. Capacity Planner: Forecasts workload against people, equipment, inventory, and time, then flags the dates where the plan stops being believable.
36. SOP Specialist: Turns successful work into clear procedures, checklists, examples, and revision-controlled operating instructions.
37. Vendor Coordinator: Tracks quotes, documents, insurance, orders, delivery dates, renewals, and vendor follow-ups in one reliable record.
38. Operations QA Auditor: Samples completed work, compares it with the promise and procedure, and routes defects to the right owner.

7. Finance: make cash, margin, and risk visible

39. Chief Financial Officer: Turns financial records and operating plans into cash, margin, forecast, risk, and capital decisions for the owner.
40. Finance Research Analyst: Gathers contracts, invoices, transactions, rates, benchmarks, and accounting definitions needed for a finance question.
41. Bookkeeping Specialist: Classifies transactions, matches receipts, prepares reconciliations, and queues uncertain entries for review.
42. Cash Flow Analyst: Projects collections and payments, highlights timing gaps, and models the cash effect of operating decisions.
43. Margin Analyst: Calculates contribution by customer, job, product, crew, or channel and traces weak margins to price, scope, waste, or mix.
44. Forecasting Specialist: Maintains rolling forecasts, compares plan with actuals, and updates scenarios when leading assumptions change.
45. Finance QA Auditor: Recalculates totals, checks source coverage, tests period and account mappings, and records reviewer approval before figures travel.

8. Technology: build and maintain the company machinery

46. Chief Technology Officer: Chooses architecture, security priorities, build-versus-buy decisions, and the technical sequence that supports the business plan.
47. Technical Research Analyst: Compares products, APIs, MCP servers, libraries, risks, and implementation paths using current primary sources.
48. Solutions Architect: Designs the flow of data, permissions, services, queues, fallbacks, and observability before code or automation spreads.
49. AI Software Developer: Builds applications, agents, integrations, tests, and interfaces from approved requirements in an isolated workspace.
50. Automation Engineer: Connects triggers, APIs, MCP tools, business rules, retries, and notifications into dependable workflows.
51. Security Reviewer: Reviews permissions, secret handling, data paths, dependencies, logs, and risky actions before systems receive broader access.
52. Software QA Auditor: Runs automated and human tests, reproduces defects, checks edge cases, and verifies the release against requirements.

9. Product: choose what deserves to be built

53. VP of Product: Balances customer evidence, business value, technical effort, and strategy to choose the product plan.
54. User Research Analyst: Synthesizes interviews, support, usage, surveys, and observation into needs, patterns, and open questions.
55. Product Strategist: Frames the customer, problem, advantage, business model, outcome, and evidence required before committing resources.
56. Requirements Writer: Converts an approved outcome into testable requirements, acceptance criteria, edge cases, and constraints.
57. UX Flow Designer: Maps the user's steps, decisions, states, errors, and recovery paths before interface details harden.
58. Release Coordinator: Tracks readiness across product, engineering, support, marketing, documentation, migration, and rollback planning.
59. Product QA Auditor: Verifies that the released experience solves the promised problem and that the evidence supports calling it done.

The seven layers of an AI employee stack

You do not need one fashionable tool from every category. You need a clean route through the categories your job actually touches.

1. The reasoning layer

This is the model that reads, writes, classifies, plans, or chooses a next step. ChatGPT and Codex, Claude, Gemini, Grok, and other models can fill this role. Choose based on the work, required tools, privacy needs, speed, cost, and evaluation results.

Do not weld the entire company to one model name. Store the employee's specification, tests, and output schema separately so the reasoning engine can be compared or changed.

2. The source-of-truth layer

This is where the employee gets current facts:

• CRM: HubSpot, Salesforce, Pipedrive, Zoho, GoHighLevel, or another customer system;
• project management: ClickUp, Asana, Monday, Trello, Jira, Linear, or Basecamp;
• work and knowledge: Google Drive, Microsoft 365, SharePoint, Dropbox, Box, Notion, or Confluence;
• operations: an ERP, field-service platform, scheduling system, inventory tool, or vertical software;
• finance: QuickBooks, Xero, Stripe, payment processors, banks, expense platforms, and approved spreadsheets;
• structured memory: PostgreSQL, Supabase, Airtable, Google Sheets, a data warehouse, or a purpose-built application database.

The best source is not always the fanciest one. It is the record the business already treats as authoritative.

3. The hands: API, webhook, connector, or MCP

An API is a direct contract with an application. It is excellent when you need a specific, stable integration and can write or maintain the code.

A webhook is the doorbell. The application sends an event when something changes: new lead, completed payment, missed call, signed contract, late task, or received text.

An automation connector is a prebuilt adapter inside Zapier, Make, n8n, or Pipedream. It is usually the fastest path when the action already exists.

An MCP server exposes approved tools and data in a standard shape an AI client can discover. The official MCP Registry calls itself a community-driven registry for MCP servers. Use it to discover candidates, then verify the publisher, permissions, and source before connecting anything important. Official MCP Registry.

Zapier says its MCP can give compatible AI clients access to thousands of applications while Zapier handles app connections and rate limits. Make can expose selected scenarios as MCP tools and scope whether the client may run or manage them. n8n can both call MCP tools and expose workflows through MCP, while still serving as the workflow engine around them. Zapier MCP, Make MCP Server, n8n documentation

MCP is not a requirement. If your employee needs one JustCall action and one CRM update, two direct APIs may be simpler than constructing a diplomatic alliance of servers.

4. The workflow layer

This layer decides what happens first, next, in parallel, after a failure, and after a person says no.

• Zapier: fast cloud automations and a large app catalog;
• Make: visual scenarios, branching, transformations, and callable MCP scenarios;
• n8n: flexible visual workflows, custom code, AI nodes, and cloud or self-hosted operation;
• Pipedream: developer-friendly workflows and API steps;
• GitHub Actions: scheduled or event-driven code jobs stored with a repository;
• custom services: TypeScript or Python workers on Vercel, Cloud Run, AWS Lambda, Azure Functions, or another host;
• durable workflow engines: Temporal, queues, or job systems when a long-running process must survive restarts and retries.

GitHub Actions supports event and schedule triggers, including timezone-aware cron schedules. That makes it a practical home for a code-based employee that must run while your laptop is closed. GitHub Actions workflow syntax.

5. The communication layer

This is where the employee reaches a customer or teammate: Gmail, Outlook, Slack, Microsoft Teams, a help desk, voice, or SMS.

The details matter.

CallRail is strong for call tracking, attribution, conversations, and call events. Its API can access calls, send texts, and create outbound calls, but its Send a Text Message endpoint explicitly limits the use to person-to-person communication and prohibits automated or bulk messaging. CallRail's own Message Flows can handle supported multi-step text automation. Use its webhooks to start an internal workflow, create a task, prepare a brief, or draft the next action without pretending every API endpoint grants every use. CallRail API, CallRail Message Flows

JustCall's API explicitly supports third-party SMS automation, scheduled sends, SMS events, and delivery updates. That can support approved workflows for new-lead responses, appointment reminders, invoice follow-up, or pre-call preparation, subject to your plan, consent, registration, and messaging rules. JustCall Send SMS/MMS, JustCall SMS events

Twilio, RingCentral, Dialpad, Aircall, and vertical communication platforms can fill similar roles. Pick the system that fits your customer record, compliance requirements, and real communication channel. A phone number is not a strategy. It is a door.

6. The publishing and paid-media layer

Buffer's current GraphQL API can create and schedule posts across connected social channels, manage content ideas, and retrieve scheduled or sent posts. A Content Production Specialist can turn one approved source into channel-specific drafts, a Marketing QA Auditor can check them, and Buffer can hold the schedule. Buffer API introduction.

For paid ads, AdKit supplies Google Ads and Meta Ads tools through MCP or its CLI. It can research keywords and audiences, browse the ad library, create campaign and ad drafts, upload images or video, and publish approved drafts. The important operating word is draft. Strategy decides what deserves budget. AdKit performs the platform work. The human owner approves publication and consequential budget changes. AdKit.

Native Google Ads and Meta Marketing APIs remain valid when you need custom control. Supermetrics, Funnel, platform exports, warehouses, and CRM revenue can support the Attribution Analyst. Do not ask the ad platform to grade its own homework using only the metrics it sold you.

7. The control layer

Every employee needs records that answer:

• What started this run?
• Which sources were used?
• What did the employee change?
• Which checks passed?
• Who approved the consequential action?
• What failed, retried, or waited?
• What business result followed?

This can begin with a run table in Supabase, Airtable, or a spreadsheet. More advanced systems may use structured logs, tracing, evaluation suites, alerts, and role-based permissions.

The purpose is not to create a tiny surveillance state for your robot interns. It is to make improvement possible. If a result cannot be traced, it cannot be coached.

Seven practical stack recipes

These are patterns, not endorsements of one vendor combination.

New-lead concierge

Route: Website form or call event → webhook → Zapier, Make, or n8n → CRM lookup and enrichment → model drafts the right response → JustCall or email sends the approved message → reply event stops the sequence → CRM stores the conversation.

Good first boundary: Let the employee classify, research, draft, and create the follow-up task. Add automatic sending only after consent rules, stop conditions, ownership, and message quality are explicit.

Pre-call preparation employee

Route: Calendar event tomorrow → fetch contact, company, open deals, recent emails, call history, and project status → research current company news → produce a cited one-page brief → deliver it in Slack, Teams, Notion, or email.

This employee never needs to pretend to close the deal. Saving the rep from opening six tabs may already pay its rent.

Invoice follow-up employee

Route: QuickBooks, Xero, Stripe, or ERP marks an invoice overdue → confirm balance, customer, dispute status, and prior contact → draft the correct reminder → send through an approved email or SMS channel → write the result back → escalate promises, disputes, and high-value accounts to a person.

Finance defines the facts. Communication tools deliver the message. The workflow remembers what already happened.

Project-control employee

Route: ClickUp, Asana, Monday, Trello, Jira, or Linear status change → compare dependencies, due dates, capacity, and client promise → flag risk → create the approved tasks → publish a concise daily exception report.

The job is not to summarize every task. The job is to reveal the few tasks that can change delivery.

Social publishing employee

Route: Approved long-form source in Drive or Notion → Content Strategist creates channel brief → Production Specialist creates variations → Marketing QA checks claims and links → Buffer schedules the approved posts → performance data returns to the next brief.

One source becomes many assets without becoming many unsupported opinions.

Paid-media testing employee

Route: Revenue goal and customer evidence → Paid Media Research Analyst builds the evidence pack → Creative Testing Strategist defines hypotheses → Media Buyer uses AdKit MCP to create Google or Meta drafts → QA checks budget, tracking, exclusions, and destinations → owner approves publication → Attribution Analyst joins spend with qualified pipeline and revenue.

The workflow separates research, buying, quality control, and approval. That is how you keep "move fast" from becoming an accounting category.

Executive morning brief employee

Route: Scheduled cloud run → calendar, inbox, CRM, project system, cash view, and unresolved decisions → source-backed summary → Chief of Staff ranks exceptions → Founder's Executive Assistant delivers one daily plan with links to the evidence.

The output should make the day easier to run. If it is twelve pages long, congratulations on creating a new meeting.

Point your AI to this page

Copy the brief below into ChatGPT, Claude, Codex, or another capable AI. You can also give it this article's URL and ask it to read the complete atlas before recommending a role.

# AI Employee Opportunity Mapper

Read this field guide first:
https://sevedgebuilds.com/blog/59-ai-employee-ideas

Act as an AI organization designer. Help me choose one useful AI employee to build first. Do not recommend building an entire AI department.

## Interview me

Ask one concise question at a time until you understand:

1. What the business sells and to whom.
2. Which repeated work consumes the most time or creates the most delay.
3. Which mistakes, missed handoffs, or slow responses cost money or trust.
4. Which tools currently hold customer, project, communication, and financial data.
5. Which actions may be automated and which require human approval.
6. What a good finished output looks like.
7. What measurable result would make a 14-day pilot worth keeping.

## Recommend the first employee

Use the 59 roles in the article as a starting atlas. You may combine parts of two roles only when the job remains narrow and clear.

Return:

- the recommended role and why it wins;
- the trigger;
- required inputs and authoritative systems;
- step-by-step specification;
- suggested APIs, webhooks, automation platforms, or MCP servers;
- state the employee must remember;
- quality checks;
- actions requiring human approval;
- exact output;
- one fallback and one escalation path;
- success metric;
- a 14-day shadow-mode pilot;
- the next role to consider only after this one works.

## Design constraints

- Prefer the simplest stack that can complete the job.
- Keep credentials outside prompts and reusable skills.
- Cite current vendor documentation for material API or MCP claims.
- Do not assume a tool permits bulk, automated, or customer-facing actions unless its terms and documentation support that use.
- Treat drafts, system updates, and customer communications as different permission levels.
- Show the handoff from this employee to the person or job that receives its output.

The downloadable version is available at the top of this page.

Build the first station

The most expensive AI employee is not the one with the largest model bill.

It is the one that creates more work than it removes.

So begin with a job that repeats, uses available facts, produces a visible artifact, and has a person who can judge it. Run it in shadow mode. Compare its output with the real work. Repair the specification. Keep a record of exceptions. Let the employee earn the next tool.

Then connect its output to the next job.

That is how a useful assistant becomes a workflow, how a workflow becomes a department, and how a collection of tools becomes a company that can actually move.

The map is not the business.

But it can finally show you where to start.