What an AI worker actually does, department by department

Product management with an AI worker on the roster

Five jobs a product team can hand to an AI teammate, and the ones it should never hand over.

The engineering work that is not writing code

Five jobs that sit between an engineer and the code, and what an AI teammate does with each.

Design work an AI teammate can take, and the part it cannot

Five jobs around the work, none of them the work itself. Taste stays where it belongs.

One analyst, thirty requests, and an AI worker in between

Five jobs that stand between a data team and the analysis they were hired to do.

Your roadmap document and your tracker disagree

A weekly diff between what the roadmap claims and what the tracker actually says.

Sixty requests, and no idea how many people asked

Clustered requests with a real count of who asked, so the argument is about value rather than recall.

Twelve interviews recorded, two of them read

Themes with participant counts and verbatim quotes, plus a flag wherever the evidence is thin.

You shipped twenty-three things and announced four

A draft built from what actually merged, plus a list of the changes nobody described.

A competitor changed their pricing and you found out in a sales call

A weekly diff of public competitor pages, reporting only what changed since last time.

The two hours before planning that nobody schedules

Carry-over, gaps and blockers assembled the day before, so the meeting is about commitment.

Forty new issues on Monday, half of them the same bug

Every new issue checked for duplicates, version and repro before an engineer opens it.

Six open pull requests and nobody knows whose turn it is

The review queue, ordered by age and named by who is blocking it, posted every morning.

The incident ended and the writeup never started

The timeline assembled from the channel and the deploy history, with the gaps left honest.

The README describes a version of the code that no longer exists

A monthly list of statements in your docs that the code no longer supports.

Twenty minutes of every design review goes on finding the file

The agenda written the day before, with last review's unresolved threads at the top.

The component was renamed and the documentation was not

A weekly drift report between the component library and the documentation that describes it.

Eight sessions recorded, and the same hesitation in six of them

Session notes turned into a task-by-task table of where people stalled and what they said.

Is this final? Asked for the fourth time this month

A completeness check before build starts, so the question is answered before it is asked.

Four versions of the logo are live and nobody signed off on three

A quarterly pass over your public surfaces, checked against the rules your brand doc states.

Can you pull the numbers, sent as a direct message at 6pm

Every ask restated as a question, with the clarifying questions asked before anyone writes SQL.

The null rate tripled in March and the board slide was already wrong

Row counts, null rates, orphans and freshness, checked every morning. Silence means clean.

The Monday metrics email that somebody writes on Sunday night

The numbers pulled and the paragraph written, delivered as a file rather than a link.

Three teams, three definitions of active user, one meeting

Every definition of a metric found and listed side by side, with the source of each.

Thirty requests in the backlog and one analyst

A scoping note per request, so the backlog is triaged on value rather than on arrival order.

Marketing work, with AI teammates on the same board

One board for the calendar, the briefs and the campaigns, with workers who draft while nobody is at a desk.

A content calendar that maintains itself between meetings

The calendar stops rotting the moment somebody other than you is responsible for updating it every week.

SEO content production, briefed once and delivered as a file

The difference between usable drafts and filler is the brief, and the brief belongs in a file the worker actually reads.

Campaign planning where the plan becomes owned tasks

Most campaigns do not fail at the idea. They fail at the fourteen small things nobody agreed to own.

Competitor monitoring that actually happens every week

Everyone agrees competitor tracking matters and nobody has done it since the last time a deal was lost over it.

A week of social posts drafted before you open the app

Drafting is the part that eats the week. Approving is the part that needs you.

Sales work, with the admin handed to an AI teammate

Selling is a conversation. Almost everything around the conversation is production work, and production work can be assigned.

A pipeline review that is assembled before the meeting

The forecast meeting is worth having. Spending the first twenty minutes reconstructing what happened is not.

Proposals drafted from your call notes, not from a template

Every proposal is 70% the same document and 30% the reason this customer is different. The 30% is the part worth your evening.

Account briefs waiting for you before the first call

Ten minutes of research changes a first call. Nobody has ten minutes before a first call.

CRM cleanup as a standing job instead of a quarterly panic

Nobody sets out to let the CRM rot. It rots because cleaning it is a four-hour job with no owner and no deadline.

Battle cards that are still true this quarter

Enablement content is written once, used constantly, and updated never. The updating is the assignable part.

Support work, with an AI teammate on the queue

The queue is a conveyor belt of small decisions. Sorting them is mechanical; making them is not.

Ticket triage that hands you a sorted queue and drafted replies

Reading forty messages to find the six that matter is the most expensive hour in a support team's day.

Help articles that keep up with the product

Every shipped change quietly makes a help article wrong, and the customer finds out before you do.

Escalations that do not go quiet after the handoff

The customer's question is not what the bug is. It is whether anyone is still looking at it.

Customer feedback that reaches product as evidence

Support already knows what is wrong with the product. The problem is the format the knowledge arrives in.

A template library that stays in your team's voice

Templates go stale the same way documentation does, except a stale template gets sent to a customer.

Running the company with an AI teammate on the reporting

The information you need to run the company exists. Assembling it every week is what nobody has time for.

The weekly review, written before the meeting starts

A meeting that begins with everyone reading the same document is a different meeting.

Board packs where the assembly is not your weekend

A board pack is 80% data you already have and 20% the story only you can tell. The 80% is what eats the week.

OKRs that stay visible after the offsite

OKRs do not fail at the writing. They fail in week three, when nobody has looked at them since the offsite.

Research memos waiting for you in the morning

The questions worth researching are the ones you never have a free afternoon for.

Every commitment from the meeting, owned and dated

The decisions were good. The problem is the eleven commitments that existed only in a document nobody reopened.

Finance work with an AI worker on the roster

The chasing, sorting and assembling that fills a finance week, prepared by a worker you brief once and review every time.

Invoice tracking that produces a chase list, not a dashboard

A worker matches Stripe payments to what you invoiced, ages the gap, and drafts the reminder for each account. You decide who actually gets chased.

Expense categorization that escalates instead of guessing

A worker pulls receipts out of the mailbox, codes them against your own chart of accounts, and puts anything ambiguous in a pile for you rather than picking a category to look finished.

A monthly close that stops drifting into week two

The close is a chase, not a calculation. A worker runs the chase: who owes what item, who has gone quiet, and what is blocking the two things that always block.

Budget reports written for the people who did the spending

Plan against actuals is easy to produce and hard to read. A worker writes the variance up in sentences a department head will actually act on.

Vendor management that catches the notice window

Most money lost on vendors is lost by missing a cancellation deadline nobody had written down. A worker keeps the register and dates the deadlines.

HR work an AI worker can prepare, and where it must stop

Scheduling, onboarding logistics, policy drafts and review-cycle admin, prepared by a worker. Every decision about a person stays with a person.

Application summaries, not candidate scores

A worker reads every application in the same shape against the criteria you published. It does not rank anyone, and it does not reject anyone.

Onboarding that is finished before the first Monday

Nobody's first day should start with an apology about accounts. A worker runs the pre-start checklist and reports what is not done while there is still time to fix it.

Interview scheduling, including the reschedules

Four calendars, two time zones, a candidate who can only do early mornings, and a panellist who declines twice. This is the job.

Policy documents that stay current and show their changes

A policy nobody has updated in three years is worse than no policy. A worker keeps the drafts moving and the versions visible. A qualified adviser signs them off.

Review cycles that finish, without a worker forming an opinion

The administration of a review cycle is enormous and the judgment inside it is entirely human. A worker takes the first part and touches none of the second.

Legal operations work an AI worker can carry

Tracking, chasing, assembling and watching. Everything a legal team spends time on that is not actually practicing law.

Knowing where every contract is, without asking three people

The question that eats a legal team's week is "where is that one now?". A worker keeps the answer current and ages every stalled agreement.

Compliance checklists with evidence attached and gaps named

A checklist where every line is ticked and nothing is evidenced is not a control. It is a document that will fail an audit slowly.

Knowing that a source changed, on the week it changed

A worker watches the public pages you nominate, quotes what changed, and dates it. What the change means for you is a question for your adviser.

A register of what you actually signed

Finance tracks what a vendor costs. Legal needs to know what you promised them, what they promised you, and which of those promises has a date on it.

Watching the open web for uses of your mark

A worker sweeps public sources on a schedule, captures dated evidence of each use it finds, and hands you a file. Whether to act is a legal decision.

Operations work with an AI worker doing the chasing

Ops is the function that holds the seams together. Most of that work is asking people things and writing down what they said.

Getting a process out of one person's head

The process exists. It is in someone's habits and in six months of Slack threads. A worker interviews and reads until it is on a page.

Procurement comparisons built from quotes, not from vendor websites

A worker researches the field, collects what the vendors actually told you, and lists the questions you have not asked yet. You choose.

Stock alerts that arrive before you are out

Polaris does not hold your inventory. A worker reads the table you already keep, compares it to what is selling, and raises a task when cover gets short.

Finding where the SOP and the real procedure came apart

Every written procedure starts accurate and drifts. A worker compares the document to how the work actually ran and reports the difference.

Dependencies as dated items, not as things people said in a meeting

Two teams agree something in a call. Neither writes it down. Three weeks later each is waiting for the other. A worker makes the promise a tracked item.