US dataswitch to UK
Securities, Commodities, and Financial Services Sales Agents
making bids or offers to buy or selling securities, developing financial plans and reviewing all securities transactions to ensure accuracy of information and conformance to governing agency regulations. If that's your week, this page is about your job.
The honest answer
Most tasks in this job are the kind AI has learned to do: monitoring markets or positions. The tasks, though, are not you.
It would be a lie to soften that; discussing financial options with clients and keeping them informed about transactions is what this work rebuilds around. The routes below start from it.
Your week, as this page understands it
Buy and sell securities or commodities in investment and trading firms, or provide financial services to businesses and individuals. May advise customers about stocks, bonds, mutual funds, commodities, and market conditions. The job title says “securities”, “commodities” or “financial services sales agents”: officially one job, several names. The real job is the part underneath: discussing financial options with clients and keeping them informed about transactions. That is the thing someone has to be right about.
The exposed part of this job is specific, and we won’t pretend it is coming back. But securities, commodities, and financial services sales agents is not one task. It is 30 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is discussing financial options with clients and keeping them informed about transactions, and the ledger below shows exactly why.
Where the work sits, by task weight
- shifting to AI
- 56%
- changing shape
- 17%
- staying human
- 26%
These bars are tasks changing hands, not people being counted out. The ledger below shows which.
Whole-job exposure score 62 out of 100 (56–68 allowing for uncertainty): high exposure, across 30 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.
How we know this
What is measured: Every published task statement for securities, commodities, and financial services sales agents is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.
How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.
Release: 2026-q4.1, scores computed 2026-08-04. Read the full method.
Your job, task by task
These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.
- 6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
Shifting to AI
17 tasksTasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.
Monitoring markets or positions
This is reading one thing and writing another: markets in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Monitor markets or positions.” (O*NET task statement)
How this row was scored
Exposure score: 100 out of 100 (96–100 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Watching prices and positions runs on live data feeds, and alerting software already does this continuously and reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Keeping accurate records of transactions
This is reading one thing and writing another: accurate records of transactions in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Keep accurate records of transactions.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Transaction records are generated straight from the firm's own trading systems, so keeping them accurate is automated work.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reporting all positions or trading results
This is reading one thing and writing another: all positions in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Report all positions or trading results.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Position and results reporting pulls straight from trading systems, so the report largely writes itself.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Making bids or offers to buy or selling securities
This is reading one thing and writing another: bids in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Make bids or offers to buy or sell securities.” (O*NET task statement)
How this row was scored
Exposure score: 63 out of 100 (56–70 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Placing buy and sell orders is already done electronically by trading software, though a registered, accountable person must stand behind the trade.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Changing shape
5 tasksTasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.
Determining customers' financial services needs and preparing proposals to sell services that address these needs
The software now makes the first pass at customers' financial services needs, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Determine customers' financial services needs and prepare proposals to sell services that address these needs.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Matching a customer's situation to services and writing the proposal is document work AI does well, with an adviser checking suitability.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Developing financial plans, based on analysis of clients' financial status
The software now makes the first pass at financial plans, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Develop financial plans, based on analysis of clients' financial status.” (O*NET task statement)
How this row was scored
Exposure score: 48 out of 100 (41–55 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Planning tools can build a solid draft plan from a client's numbers, but a qualified adviser normally shapes and signs it.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Contacting prospective customers to present information and explain available services
The software now makes the first pass at prospective customers, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Contact prospective customers to present information and explain available services.” (O*NET task statement)
How this row was scored
Exposure score: 46 out of 100 (39–53 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; the value is that a specific person does it.
The rating behind it: AI can prepare and even make the approach, but winning a prospect's attention still leans on a person.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Staying human
8 tasksTasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.
Agreeing on buying or selling prices at optimal levels for clients
The rules require a named, qualified person to answer for buying, and that person cannot be a piece of software.
importance 5 · CoreSource: “Agree on buying or selling prices at optimal levels for clients.” (O*NET task statement)
How this row was scored
Exposure score: 39 out of 100 (32–46 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Software already works out the best price levels, but a regulated broker still has to agree the deal with the client.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Discussing financial options with clients and keeping them informed about transactions
The rules require a named, qualified person to answer for financial options, and that person cannot be a piece of software.
importance 4 · CoreSource: “Discuss financial options with clients and keep them informed about transactions.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Explaining choices and keeping clients updated mixes regulated advice with a personal relationship, so a licensed adviser stays central.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 3/4 · how much data exists 3/4.
Interviewing clients to determine clients' assets
The rules require a named, qualified person to answer for clients, and that person cannot be a piece of software.
importance 4 · CoreSource: “Interview clients to determine clients' assets, liabilities, cash flow, insurance coverage, tax status, or financial objectives.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: People share their full financial picture with someone they trust, so this discovery conversation stays largely human despite online forms.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 3/4 · how much data exists 3/4.
Show the other 20 tasks
Preparing and sending requests for price quotations to all companies in a particular market
shifting to AIThis is reading one thing and writing another: requests in, a record out. That is the shape today's tools are built for.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Prepare and send requests for price quotations to all companies in a particular market.” (O*NET task statement)
How this row was scored
Exposure score: 100 out of 100 (96–100 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Sending quote requests is a standard, repeatable message to a known list of firms, already handled by electronic platforms.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Evaluating costs and revenue of agreements to determine continued profitability
shifting to AIThis is reading one thing and writing another: costs in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Evaluate costs and revenue of agreements to determine continued profitability.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (86–100 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Comparing an agreement's costs against the revenue it brings in is spreadsheet analysis on data the firm already holds.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Calculating costs for billings or commissions
shifting to AIThis is reading one thing and writing another: costs in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Calculate costs for billings or commissions.” (O*NET task statement)
How this row was scored
Exposure score: 93 out of 100 (89–97 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Commission and billing figures follow set formulas applied to transaction data, which software already calculates automatically.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Relaying buy or selling orders to securities exchanges or to firm trading departments
shifting to AIThis is reading one thing and writing another: buy in, a record out. That is the shape today's tools are built for.
importance 4 · SupplementalSource: “Relay buy or sell orders to securities exchanges or to firm trading departments.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Routing buy and sell orders to exchanges and trading desks is already a fully electronic, automated process.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Pricing securities or commodities based on market conditions
shifting to AIThis is reading one thing and writing another: securities in, a record out. That is the shape today's tools are built for.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Price securities or commodities based on market conditions.” (O*NET task statement)
How this row was scored
Exposure score: 88 out of 100 (84–92 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Pricing off live market conditions is model-driven maths that software does continuously and reliably.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Informing other traders, managers or customers of market conditions, including volume, price, competition or dynamics
shifting to AIThis is reading one thing and writing another: other traders, managers or customers of market conditions in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Inform other traders, managers, or customers of market conditions, including volume, price, competition, or dynamics.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Market updates are assembled from live data feeds in a standard format, so software can prepare and share them instantly.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Explaining stock market terms or trading practices to clients
shifting to AIThis is reading one thing and writing another: stock market terms in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Explain stock market terms or trading practices to clients.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Market terms and trading practices are standard, well-documented material that AI can explain clearly and on demand.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Supplying the latest price quotes on any security
shifting to AIThis is reading one thing and writing another: the latest price quotes in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Supply the latest price quotes on any security, as well as information on the activities or financial positions of the corporations issuing these securities.” (O*NET task statement)
How this row was scored
Exposure score: 85 out of 100 (81–89 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Quotes and company financials are live published data that systems can look up and pass on instantly.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Tracking and analyzing factors that affect price movement
shifting to AIThis is reading one thing and writing another: factors in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Track and analyze factors that affect price movement, such as trade policies, weather conditions, political developments, or supply and demand changes.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: News, weather and trade data are all digital and AI pulls them together well, though weighing what matters takes experience.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Preparing financial reports to monitor client or corporate finances
shifting to AIThis is reading one thing and writing another: financial reports in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Prepare financial reports to monitor client or corporate finances.” (O*NET task statement)
How this row was scored
Exposure score: 81 out of 100 (77–85 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Financial reports are assembled from data the firm already holds, and generating them is routine automated work.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Completing sales order tickets and submitting for processing of client-requested transactions
shifting to AIThis is reading one thing and writing another: sales order tickets in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Complete sales order tickets and submit for processing of client-requested transactions.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Filling in and submitting an order form from a client's instruction is routine data entry inside a supervised system.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Buying or selling stocks, bonds, commodity futures, foreign currencies or other securities on behalf of investment dealers
shifting to AIThis is reading one thing and writing another: stocks, bonds, commodity futures in, a record out. That is the shape today's tools are built for.
importance 5 · CoreSource: “Buy or sell stocks, bonds, commodity futures, foreign currencies, or other securities on behalf of investment dealers.” (O*NET task statement)
How this row was scored
Exposure score: 63 out of 100 (56–70 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Execution itself is highly automated, but trading for a dealer requires a registered person who is accountable for it.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Devising trading, option or hedge strategies
shifting to AIThis is reading one thing and writing another: option in, a record out. That is the shape today's tools are built for.
importance 4 · CoreSource: “Devise trading, option, or hedge strategies.” (O*NET task statement)
How this row was scored
Exposure score: 62 out of 100 (55–69 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Standard hedging and options strategies are well documented and easy for software to construct, though a licensed specialist approves them.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Purchasing or selling financial derivatives for customers
changing shapeThe software now makes the first pass at financial derivatives, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Purchase or sell financial derivatives for customers.” (O*NET task statement)
How this row was scored
Exposure score: 53 out of 100 (46–60 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Execution is automated, but trading derivatives for customers requires a licensed, accountable person handling the account.
The five ratings: output a model can produce 4/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.
Reviewing all securities transactions to ensure accuracy of information and conformance to governing agency regulations
changing shapeThe software now makes the first pass at all securities transactions, but someone has to be answerable for the result, and it cannot be the software. So the job becomes checking and deciding rather than producing.
importance 4 · CoreSource: “Review all securities transactions to ensure accuracy of information and conformance to governing agency regulations.” (O*NET task statement)
How this row was scored
Exposure score: 52 out of 100 (45–59 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; someone qualified has to answer for it.
The rating behind it: Automated checks catch errors and rule breaches well, but a registered supervisor has to sign off the review itself.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Identifying opportunities or developing channels for purchase or sale of securities or commodities
staying humanThe value here is that a specific person handles opportunities and stands behind it. That is earned, not computed.
importance 4 · CoreSource: “Identify opportunities or develop channels for purchase or sale of securities or commodities.” (O*NET task statement)
How this row was scored
Exposure score: 35 out of 100 (28–42 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Software is good at spotting trading opportunities in data, but building the business relationships that open deal channels needs people.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Selling services or equipment, such as trusts, investments or checking processing services
staying humanThe rules require a named, qualified person to answer for services, and that person cannot be a piece of software.
importance 3 · SupplementalSource: “Sell services or equipment, such as trusts, investments, or check processing services.” (O*NET task statement)
How this row was scored
Exposure score: 24 out of 100 (17–31 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Closing a sale of financial services rests on a trusted relationship with the buyer, even though supporting material can be automated.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 3/4 · how much data exists 3/4.
Negotiating prices or contracts for securities or commodities sales or purchases
staying humanThe rules require a named, qualified person to answer for prices, and that person cannot be a piece of software.
importance not publishedO*NET hasn't yet published importance ratings for this occupation's tasks, so the ordering here is ours, not theirs.
Source: “Negotiate prices or contracts for securities or commodities sales or purchases.” (O*NET task statement)
How this row was scored
Exposure score: 21 out of 100 (14–28 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Negotiating terms turns on reading the other side in a live exchange, and the deciding context is private rather than documented.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Offering advice on the purchase or sale of particular securities
staying humanThe rules require a named, qualified person to answer for advice, and that person cannot be a piece of software.
importance 4 · CoreSource: “Offer advice on the purchase or sale of particular securities.” (O*NET task statement)
How this row was scored
Exposure score: 20 out of 100 (13–27 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Recommending specific investments is reserved for licensed advisers and depends on a trusted relationship with that particular client.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 3/4 · needs to be trusted in the moment 3/4 · how much data exists 3/4.
Supervising support staff and ensuring proper execution of contracts
staying humanThe rules require a named, qualified person to answer for support staff, and that person cannot be a piece of software.
importance 4 · SupplementalSource: “Supervise support staff and ensure proper execution of contracts.” (O*NET task statement)
How this row was scored
Exposure score: 13 out of 100 (6–20 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: someone qualified has to answer for it; the value is that a specific person does it.
The rating behind it: Managing a team and holding people to contract terms depends on personal authority and relationships that software cannot take over.
The five ratings: output a model can produce 1/4 · needs a body in a room 0/4 · needs an accountable person 2/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
What this job pays, and how many people do it
- Median pay
- $78,660a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
- People doing this job
- 489,570in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)
What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.
Why this is shifting
The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: accurate records of transactions in, a record out. The rows above are exactly that shape: monitoring markets or positions and keeping accurate records of transactions. What it cannot do is be answerable: financial options need a named person the rules will accept, and software cannot be that person. Which is why this page talks about your tasks changing, not your job ending.
Your move
Over a pint: what I’d tell you if you were my friend
The exposed part of your job is the biggest part, and I am not going to dress that up: monitoring markets or positions is work today's tools do quickly and cheaply, and that is not coming back.
So, given all that: 56% of this job's task weight sits in rows the software is already learning, 17% in rows that change shape rather than disappear, and 26% in rows it is nowhere near. That is the position, measured across 30 scored tasks. It is not a forecast about you.
What you have that the software does not is discussing financial options with clients and keeping them informed about transactions, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.
This week: one thing
Sit on the machine's side of the desk. Pick one real piece of accurate records of transactions you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.
- What you end up holding
- a written list of the machine’s mistakes, in your handwriting
- How long it takes
- an evening, or an hour if you pick one job rather than one client
If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of accurate records of transactions, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.
Over the next 90 days
Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is monitoring markets or positions” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.
Over the next 12 months
Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of discussing financial options with clients and keeping them informed about transactions you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.
The roads out of here, and why I am not sending you down them
I looked at the obvious moves out of this job, and here is what I found.
I checked the 12 nearest US occupations to securities, commodities, and financial services sales agents (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was personal financial advisors: only about 10% of its durable work is work you already do. I am not going to pretend that is comfortable news: 56% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “agree on buying or selling prices at optimal levels for clients” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.
How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.
3 moves I checked and rejected
These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.
Personal Financial Advisors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already interview clients to determine clients' assets, liabilities, cash flow, insurance coverage, tax status…, and their equivalent is to interview clients to determine their current income, expenses, insurance coverage, tax status, financial…. Across both published task lists that is about 10% of the durable work in that job.
Why I am not recommending it: You would be starting most of it from nothing: about 10% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Sales Representatives of Services, Except Advertising, Insurance, Financial Services, and Travel
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already contact prospective customers to present information and explain available services, and their equivalent is to contact prospective or existing customers to discuss how services can meet their needs. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step. It is a pay cut, in those words: $69,990 against your $78,660, 11.0% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice.
Accountants and Auditors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already keep accurate records of transactions, and their equivalent is to examine records and interview workers to ensure recording of transactions and compliance with…. Across both published task lists that is about 4% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 4% of the durable side of that job. That is a different job, not a next step.
What I’d stop worrying about
A friend tells you what not to spend fear on. This is that list.
The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 56% of its task weight, across 30 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: discussing financial options with clients and keeping them informed about transactions is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.
You are reading the United States figures
The United Kingdom splits this work across more than one official group, of which Brokers is the closest. The pay and employment figures are not directly comparable, and we do not average them together.
Switch to the United Kingdom page →partial match
In UK official statistics this job is counted as Brokers. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.
Your route through this
Where to go next, and what it costs
Free, and complete
The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.
Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
Anywhere in the US:
An American Job Center will sit down with you for free. Find yours by ZIP code.
Free
Anywhere in the US:
CareerOneStop - Licensed occupations finder
Check what your state actually requires before you pay for anything.
Free
Anywhere in the US:
Free
No Space for this job, but one for what is happening to it
Nothing Collab365 runs is built for securities / commodities / financial services sales agents, and we are not going to point you at the nearest one and call it a fit.
There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 56% of the work on this page is already inside what they can do.
7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.
The AI Authority is a general community about working with AI, not a course for securities / commodities / financial services sales agents. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.
Noted, and thank you. We’ll email you if a Space for securities / commodities / financial services sales agents launches. Nothing else.
That did not look like an email address, so nothing was saved. Have another go below.
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No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.
Questions people ask about this job
- Will AI replace Securities, Commodities, and Financial Services Sales Agents?
- Not as a job, but it is already doing parts of the work. Across the 30 official task statements scored for Securities, Commodities, and Financial Services Sales Agents (United States, SOC 41-3031), 56% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 62 out of 100 (range 56–68, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
- Which tasks in “Securities, Commodities, and Financial Services Sales Agents” can AI already do?
- The highest-scoring tasks in release 2026-q4.1 are: “Monitor markets or positions” (100/100, very high); “Prepare and send requests for price quotations to all companies in a particular market” (100/100, very high); “Keep accurate records of transactions” (93/100, very high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
- Which tasks in “Securities, Commodities, and Financial Services Sales Agents” stay human?
- About 26% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Supervise support staff and ensure proper execution of contracts” (13/100, minimal); “Offer advice on the purchase or sale of particular securities” (20/100, low); “Discuss financial options with clients and keep them informed about transactions” (20/100, low). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
- What should someone working in “Securities, Commodities, and Financial Services Sales Agents” do about AI?
- Start from the ledger rather than the headline: 56% of this job's weighted core work is exposed, and roughly 26% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
- How is the AI exposure score for Securities, Commodities, and Financial Services Sales Agents calculated?
- Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 30 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.
Where these numbers come from
Worth knowing about these figures
- The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
- 6 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
- Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.
- Task statements
- onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
- Task weights
- onet-db (im-rt-with-imputed)
- Scores
- Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-04.
- Pay and employment
- bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))
Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.
The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.
The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.
Using these figures?
Cite this
Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.
Plain text
Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).
BibTeX
@misc{collab365futureproof2026q41,
title = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
author = {{Collab365}},
year = {2026},
url = {https://futureproof.collab365.com/data/2026-q4.1},
note = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}Data as of release 2026-q4.1, published . Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.