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Will AI replace brokerage clerks?

A little.

Much of the posting and calculating follows set rules, but failed trades, account questions and audit sign-off still need a person. This job scores 62 out of 100 on (higher is safer). Today AI could do about 12% of the work by itself, people do 64% with AI’s help, and 24% still needs a person.

Updated 3 October 2026 43-4011 4133 2026-Q4
Office and Administrative SupportBrokerage Clerks43-4011 · 2026-Q4
12% AI does it64% AI helps24% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 24%AI helps 64%AI does it 12%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Why the settlement desk still runs through a person

Will AI replace brokerage clerks? Not outright, and the reason sits in the task mix. A large part of this job follows set rules: computing total holdings, dividends, commissions and interest, then recording those transactions in the firm’s systems. Software has chipped away at that work for years. What remains is everything that happens when the rules run out — a trade that will not settle, a confirmation that does not match the order, a client asking why their account balance looks wrong.

The second reason is accountability. Brokerage records are audited, and firms want a named employee who can explain a correction, show the paper trail and sign off on a fix. A model can draft the explanation. It cannot carry the responsibility, and it cannot call a transfer agent at another firm to chase a stuck security.

The honest pressure here is not the whole job disappearing. It is task erosion plus thinner hiring at the bottom. The Bureau of Labor Statistics projects employment in this occupation to fall 7.6% between 2025 and 2035, from about 35,940 jobs, with median pay of $65,750 (BLS, 2025). Fewer desks, more work per desk, and fewer openings for someone starting out.

What AI handles, what it drafts, and what lands on the clerk

Start with the work AI can already take. Our task review puts 12% of task time in that group: calculating commissions, interest and dividend amounts, and keying or updating transaction records. These steps have clear inputs, clear outputs and a check that can be run automatically. Coverage, our measure of how much task time AI can handle today, reads 44 out of 100 for this job, and the coverage scoring method explains how that is built.

Next comes the assisted group, 64% of task time. Monitoring daily price and market data and turning it into a client report is a good example. So is preparing the forms and paperwork for a transfer of securities: a tool can fill the fields and flag a gap, while the clerk confirms the details are right before anything leaves the firm.

Then there is the work our review leaves with people, 24% of task time. Answering customer questions about account status and activity sits here, because the answer often depends on judgment about what went wrong. Resolving discrepancies on a trade sits here too. Both involve other parties, incomplete information and a decision someone has to own.

How strong is the evidence on this job?

Thin, and we say so. The evidence grade for brokerage clerks is D, which means there is no published head-to-head test of AI against a qualified clerk doing this work. Benchmarks on document extraction and spreadsheet math tell you something about the easier parts of the day. They do not tell you how a system performs on a failed settlement with mismatched records from two institutions.

What would settle it: a clean benchmark built from real settlement exceptions, scored for accuracy and for how often the system escalates; or a firm publishing error rates and throughput on the same queue before and after automation, measured against staff doing the same queue. Until something like that exists, we give no parity number, and the quality parity method sets out why a grade of that kind never gets one.

When could the work change?

Most likely between 2035 and 2047 (8 in 10 of our scenarios). The replacement year method explains what that window measures and how the range is produced.

Two things could pull it earlier. First, straight-through processing: every extra piece of the trade lifecycle that moves machine-to-machine removes clerical touchpoints across the whole desk, not one task at a time. Second, cost. The cost panel above compares running software on these tasks with staffing the work, and that comparison is a steady push on back-office budgets.

Two things hold it back. Recordkeeping and audit rules mean firms need traceable decisions and a person who can defend them to an examiner. And exceptions cross firm boundaries, so a fix often depends on another institution’s timing and systems rather than your own. The physical side of the job is minor and already served by fixed automation — scanners, printers, document handling — so robotics is not the lever here.

What to do: if your week is mostly posting and calculating, ask to be put on the exceptions queue, where the judgment work sits.

How to stay needed on a brokerage desk

Lean into the tasks our review leaves with people. Own the resolution of trade and account discrepancies end to end. Be the person clients and advisors get handed to when an account question is complicated. Take the coordination work with transfer agents, custodians and other firms, since that is where the job turns into negotiation rather than data entry.

Two skills pay for themselves. One is regulatory reading: knowing which rule applies to a correction and what the record has to show. The other is working with the firm’s data directly — reconciliation queries, basic scripting, and checking what an automated tool produced instead of trusting it. Both make you the reviewer rather than the input.

If you are weighing a move, nearby desks are worth a look: Credit Authorizers, Checkers, and Clerks, New Accounts Clerks, and Bookkeeping, Accounting, and Auditing Clerks. You can also read across the information and record clerks family, see how the wider finance and insurance sector looks, or put two jobs side by side on our compare tool. Our entry-level hiring tracker is the one to watch if you are starting out, and the full scoring method shows how every figure on this page is built.

Frequently asked questions

Can trading be replaced by AI?

Much of trade execution is already automated, and has been for years. Algorithmic and electronic trading routes orders faster than any person could. What is not automated is the decision chain around it: mandate, risk limits, client suitability and accountability when something breaks. For clerical staff, the point is narrower. Execution is machine work; settlement exceptions and client explanations still land on a desk.

Will AI take over investment banking?

Banking roles are seeing tasks move, not whole functions vanish. Drafting, data gathering, comparable company tables and first-pass models are the parts tools handle best, which is exactly the work junior staff used to cut their teeth on. Client relationships, negotiation and sign-off stay with people. The bigger change reported across finance is fewer junior hires per senior banker, not empty floors.

Is AI a threat to finance jobs?

It is a threat to repetitive finance tasks more than to finance careers. Posting, reconciliation, invoice matching and basic reporting are the easiest things to automate, and back-office roles carry a lot of them. Jobs built on exception handling, client judgment and regulatory accountability hold up better. You can compare how different finance roles score across our rankings and sector pages.

Which jobs will not be replaced by AI?

The ones where most of the time goes on physical work, in-person judgment, or decisions someone has to answer for legally. Skilled trades, hands-on healthcare and roles with real accountability sit at the safer end. Office roles built around structured data sit lower. Our safest jobs list and rankings show where each occupation falls and what evidence sits behind it.

What does a brokerage clerk actually do?

Day to day, the job supports trades after they are placed. That means recording transactions, computing holdings, dividends, commissions and interest, preparing securities transfer paperwork, checking confirmations against orders and sorting out anything that does not match. Clerks also field account questions from clients and advisors. The task list above shows which of those steps AI can handle, assist with, or leave alone.

Should brokerage clerks retrain?

Not necessarily retrain from scratch. The practical move is shifting your weight inside the role: toward exception resolution, compliance-aware corrections and reviewing automated output. If you do want to move, operations analysis, compliance support and accounting roles use the same knowledge. The related jobs linked on this page are the closest matches by the kind of work involved.

Each ridge is a slice of the job's task time.Needs a human 24%AI helps 64%AI does it 12%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Brokerage Clerks, O*NET-SOC 43-4011. 24% of the job’s task time still needs a human, so 24 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 24% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 24%AI helps 64%AI does it 12%
The job's task list: the parts AI can do are blacked out.Needs a human 24%AI helps 64%AI does it 12%
Correspond with customers and confer with coworkers to answer inquiries, discuss market fluctuations, or resolve account problems.AI helps
Document security transactions, such as purchases, sales, conversions, redemptions, or payments, using computers, accounting ledgers, or certificate records.AI does it
File, type, or operate standard office machines.Needs a human
Perform clerical tasks, such as answering phones or distributing mail.Needs a human
Prepare forms, such as receipts, withdrawal orders, transmittal papers, or transfer confirmations, based on transaction requests from stockholders.AI helps
Schedule and coordinate transfer and delivery of security certificates between companies, departments, and customers.AI helps
Monitor daily stock prices and compute fluctuations to determine the need for additional collateral to secure loans.AI helps
Verify ownership and transaction information and dividend distribution instructions to ensure conformance with governmental regulations, using stock records and reports.AI helps
Compute total holdings, dividends, interest, transfer taxes, brokerage fees, or commissions and allocate appropriate payments to customers.AI helps
Prepare reports summarizing daily transactions and earnings for individual customer accounts.AI helps

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: 2035–2047

Most likely between 2035 and 2047 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
A little.
By 2045
100%
of our scenarios have AI largely doing this job by 2045 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)
By 2060
100%
of our scenarios have AI largely doing this job by 2060 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could do a little of this job (A little.)100%Today2030: 100.0% of scenarios: AI could partly do this job (Partly.)100%20302035: 20.0% of scenarios: AI could partly do this job (Partly.)20%2035: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2035: 40.0% of scenarios: AI could largely do this job (Largely.)40%20352040: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2040: 70.0% of scenarios: AI could largely do this job (Largely.)70%20402045: 100.0% of scenarios: AI could largely do this job (Largely.)100%20452050: 100.0% of scenarios: AI could largely do this job (Largely.)100%20502055: 100.0% of scenarios: AI could largely do this job (Largely.)100%20552060: 100.0% of scenarios: AI could largely do this job (Largely.)100%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%100.0%0.0%
20300.0%0.0%100.0%0.0%0.0%
203540.0%40.0%20.0%0.0%0.0%
204070.0%30.0%0.0%0.0%0.0%
2045100.0%0.0%0.0%0.0%0.0%
2050100.0%0.0%0.0%0.0%0.0%
2055100.0%0.0%0.0%0.0%0.0%
2060100.0%0.0%0.0%0.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.2 out of 5 for consequence and decisions 3.9 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 4.7 and physical closeness 3.7 out of 5; caring for or serving people is 2.0 out of 5 in importance.
LicensingUsual entry requirement (BLS): high school diploma or equivalent, then moderate-term on-the-job training; 2 task statements mention a licence or certification.
Physical work24% of the task time is physical; robots have been shown on 100% of that time.
RegulationWorkers rate responsibility for others' health and safety 1.4 out of 5.

What would it cost to hand the work to AI?

The share of the year AI could handle (917 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$90–$9,170
A person’s wage for the same hours
$22,160–$44,990

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

24%
of the task time is physical work
Fixed automation
the kind of robot the physical work would need
Mature and widely deployed in factories and warehouses, but the work has to be redesigned around the machine.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 24%AI helps 64%AI does it 12%
Writing · 40.9% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 26.5% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 0% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 12.2% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 8.2% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 12.2% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 0% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 24%AI helps 64%AI does it 12%
How exposed is it?

Still needs a human: 62/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 24% needs a human, 64% AI helps, 12% AI does it. Still needs a human: 62/100 ↑ safer. Will AI replace them? A little.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 62/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

AI will automate many routine brokerage clerk tasks like data entry, reconciliation, and document processing, but humans will still be needed for oversight, exceptions, compliance, and client-facing coordination.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudePartly

AI will automate many routine brokerage clerk tasks like trade settlement and record-keeping, but human oversight will likely remain necessary for exception handling, compliance, and client relations.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI will automate routine data entry, transaction processing, and record-keeping tasks, human clerks will still be needed to handle complex exceptions, client relationships, and regulatory compliance.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will likely eliminate many routine brokerage-clerk tasks and reduce staffing, but humans will remain for exceptions, compliance, and complex cases.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Brokerage Clerks? A little. Still needs a human: 62/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/brokerage-clerks/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.