Will AI replace Buyers and procurement officers?

Not as a job, but it is already doing parts of the work. Across the 40 official task statements scored for Buyers and procurement officers (United Kingdom, SOC 3551), 53% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 56 out of 100 (range 51–61, band: partial). 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 “Buyers and procurement officers” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Analyse sales figures and trends” (93/100, very high); “Extract data from financial records to inform purchasing decisions” (93/100, very high); “Approve invoices for procurement and purchasing activities” (88/100, 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 “Buyers and procurement officers” stay human?

About 25% 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: “Inspect products to ensure they meet specifications” (0/100, minimal); “Develop and maintain professional relationships with stakeholders and senior managers” (2/100, minimal); “Attend meetings to network with peers in purchasing” (4/100, minimal). 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 “Buyers and procurement officers” do about AI?

Start from the ledger rather than the headline: 53% of this job's weighted core work is exposed, and roughly 25% 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 Buyers and procurement officers 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 40 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.

UK dataswitch to US

Buyers and procurement officers

purchasing merchandise that meets organisational specifications, designing tender documents to solicit supplier bids and maintaining accurate records. If that's your week, this page is about your job.

The honest answer

This job is splitting in two: approving invoices for procurement and purchasing activities is work AI now does quickly and cheaply, and attending trade fairs, in the UK and overseas, to select and assemble a new collection of products is work it can't touch.

Your move: what you can actually do about this ↓

Where the work sits, by task weight

shifting to AI: 53%
changing shape: 23%
staying human: 25%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 56 out of 100 (51–61 allowing for uncertainty): partial exposure, across 40 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 buyers and procurement officers 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.

Which half fills your week decides your exposure. That is more in your control than it sounds.

Your week, as this page understands it

Buyers and procurement officers organise and undertake the buying of raw materials, equipment and merchandise from manufacturers, importers, wholesalers and other sources for distribution, resale or for own internal use. The job title says “buyers” or “procurement officers”: officially one job, two names. The real job is the part underneath: attending trade fairs, in the UK and overseas, to select and assemble a new collection of products. 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 buyers and procurement officers is not one task. It is 40 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is attending trade fairs, in the UK and overseas, to select and assemble a new collection of products, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 53%
changing shape: 23%
staying human: 25%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

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.

23 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

21 tasks

Tasks 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.

Approving invoices for procurement and purchasing activities
This is reading one thing and writing another: invoices in, a record out. That is the shape today's tools are built for.
importance 90 · 3551/00
Source: “Approve invoices for procurement and purchasing activities.” (UK 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: Matching invoices to orders and deliveries is already automated in most finance systems, with a person approving anything unusual.
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.
Evaluating contract terms, conditions and obligations to ensure delivery and supplier performance
This is reading one thing and writing another: contract terms, conditions and obligations in, a record out. That is the shape today's tools are built for.
importance 90 · 3551/00
Source: “Evaluate contract terms, conditions, and obligations to ensure delivery and supplier performance.” (UK task statement)
How this row was scored
Exposure score: 66 out of 100 (62–70 allowing for uncertainty): 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: Reading contracts against obligations and delivery records is document work that software now does quickly and to a usable standard.
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 0/4 · how much data exists 3/4.
Authorising payments and merchandise returns
This is reading one thing and writing another: payments in, a record out. That is the shape today's tools are built for.
importance 85 · 3551/00
Source: “Authorise payments and merchandise returns.” (UK task statement)
How this row was scored
Exposure score: 72 out of 100 (65–79 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; mistakes that are cheap to catch.
The rating behind it: Most approvals follow set limits and rules that systems apply automatically, with a named person accountable for the exceptions.
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 0/4 · how much data exists 4/4.
Analysing sales figures and trends
This is reading one thing and writing another: sales figures in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Analyse sales figures and trends.” (UK 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: Spotting patterns in sales figures is exactly what spreadsheets and analysis tools are built for.
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.

Changing shape

9 tasks

Tasks 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.

Purchasing merchandise that meets organisational specifications
The software now makes the first pass at merchandise, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 95 · 3551/00
Source: “Purchase merchandise that meets organisational specifications.” (UK task statement)
How this row was scored
Exposure score: 56 out of 100 (52–60 allowing for uncertainty): partial 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: Matching purchases to written specifications is comparison work that procurement systems increasingly do automatically.
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 1/4 · how much data exists 3/4.
Buying merchandise or commodities for resale to wholesale or retail consumers
The software now makes the first pass at merchandise, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 95 · 3551/00
Source: “Buy merchandise or commodities for resale to wholesale or retail consumers.” (UK 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; mistakes that are cheap to catch.
The rating behind it: Choosing what to buy for resale is analysis of sales data, though suppliers are often met in person.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Contributing to procurement decision making to ensure value for money
The software now makes the first pass at procurement decision, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 3551/00
Source: “Contribute to procurement decision making to ensure value for money.” (UK task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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; mistakes that are cheap to catch.
The rating behind it: Cost comparisons and scoring models are exactly what software is good at, though a buyer weighs the trade-offs and answers for the choice.
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 1/4 · how much data exists 3/4.

Staying human

10 tasks

Tasks 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.

Negotiating orders with suppliers
The value here is that a specific person handles orders and stands behind it. That is earned, not computed.
importance 90 · 3551/00
Source: “Negotiate orders with suppliers.” (UK 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 value is that a specific person does it.
The rating behind it: AI can prepare the numbers and options, yet supplier deals still turn on a person doing the haggling.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Ensuring ethical, sustainable and legal sourcing of product ranges, aligned with business strategy
The ratings behind this row put ethical, sustainable and legal sourcing of product ranges well outside what today's tools can do on their own.
importance 85 · 3551/00
Source: “Ensure ethical, sustainable, and legal sourcing of product ranges, aligned with business strategy.” (UK task statement)
How this row was scored
Exposure score: 28 out of 100 (21–35 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Supplier screening tools help a lot, but proving a supply chain is genuinely ethical relies on private information and site visits.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Establishing and maintaining strong collaborative relationships with customers
The value here is that a specific person handles strong collaborative relationships and stands behind it. That is earned, not computed.
importance 80 · 3551/00
Source: “Establish and maintain strong collaborative relationships with customers, suppliers, and stakeholders.” (UK task statement)
How this row was scored
Exposure score: 10 out of 100 (6–14 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Long-term working relationships with customers and suppliers are the whole point of this task.
The five ratings: output a model can produce 1/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 4/4 · how much data exists 2/4.

Show the other 30 tasks

Extracting data from financial records to inform purchasing decisions
shifting to AI
This is reading one thing and writing another: data in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Extract data from financial records to inform purchasing decisions.” (UK 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: Pulling figures out of financial records is routine data extraction that systems already handle.
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.
Monitoring and analysing sales records
shifting to AI
This is reading one thing and writing another: sales records in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Monitor and analyse sales records, trends, or economic conditions to anticipate consumer buying patterns, company sales, and needed inventory.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Spotting sales trends and forecasting demand from records is standard analysis that software does quickly.
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.
Researching potential business opportunities for procurement
shifting to AI
This is reading one thing and writing another: potential business opportunities in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Research potential business opportunities for procurement.” (UK task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 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: Scanning markets for supply opportunities is research over widely published sources.
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.
Designing tender documents to solicit supplier bids
shifting to AI
This is reading one thing and writing another: tender documents in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Design tender documents to solicit supplier bids.” (UK 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: Tender documents follow standard templates and clause libraries, which is exactly what drafting tools do well.
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.
Verifying compliance of bids with specified rules and guidelines
shifting to AI
This is reading one thing and writing another: compliance of bids in, a record out. That is the shape today's tools are built for.
importance 75 · 3551/00
Source: “Verify compliance of bids with specified rules and guidelines.” (UK 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: Checking bids against a stated rulebook is systematic comparison work software does 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 3/4.
Submitting tender documents
shifting to AI
This is reading one thing and writing another: tender documents in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Submit tender documents.” (UK 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: Assembling and submitting a tender pack against a checklist is structured document 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.
Responding to procurement-related enquiries as a first line of action
shifting to AI
This is reading one thing and writing another: procurement-related enquiries in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Respond to procurement-related enquiries as a first line of action.” (UK task statement)
How this row was scored
Exposure score: 79 out of 100 (75–83 allowing for uncertainty): 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: First-line procurement questions follow familiar patterns software answers from policy and system data.
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 3/4.
Maintaining accurate records
shifting to AI
This is reading one thing and writing another: accurate records in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Maintain accurate records.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Keeping records accurate is routine screen work software does reliably.
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 3/4.
Analysing consumer data to identify and forecast market trends
shifting to AI
This is reading one thing and writing another: consumer data in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Analyse consumer data to identify and forecast market trends.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Spotting and forecasting trends in consumer data is a standard analysis job for software.
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 3/4.
Determining and recommending specific mark-up and mark-down rates to optimise merchandise selling prices
shifting to AI
This is reading one thing and writing another: specific mark-up in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Determine and recommend specific mark-up and mark-down rates to optimise merchandise selling prices.” (UK task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): 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: Working out mark-ups and mark-downs from sales data is a pricing calculation software handles well.
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 3/4.
Monitoring consumer preferences to determine the best way to introduce new eco-friendly products
shifting to AI
This is reading one thing and writing another: consumer preferences in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Monitor consumer preferences to determine the best way to introduce new eco-friendly products.” (UK 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; mistakes that are cheap to catch.
The rating behind it: Reading consumer trends to plan a product launch is research and analysis AI does well.
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 3/4.
Identifying opportunities to purchase and resell carbon-neutral products to consumers
shifting to AI
This is reading one thing and writing another: opportunities in, a record out. That is the shape today's tools are built for.
importance 60 · 3551/00
Source: “Identify opportunities to purchase and resell carbon-neutral products to consumers.” (UK 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; mistakes that are cheap to catch.
The rating behind it: Finding carbon-neutral products worth stocking is market research AI can do thoroughly and quickly.
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 3/4.
Soliciting bid proposals from suppliers
shifting to AI
This is reading one thing and writing another: bid proposals in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Solicit bid proposals from suppliers.” (UK task statement)
How this row was scored
Exposure score: 74 out of 100 (70–78 allowing for uncertainty): 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: Putting out a request for quotes is templated work that procurement systems already generate and send to supplier lists.
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 1/4 · how much data exists 4/4.
Managing a portfolio of products and services to adhere to critical paths
shifting to AI
This is reading one thing and writing another: a portfolio of products in, a record out. That is the shape today's tools are built for.
importance 80 · 3551/00
Source: “Manage a portfolio of products and services to adhere to critical paths.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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; mistakes that are cheap to catch.
The rating behind it: Tracking a product portfolio against deadlines is structured scheduling work that software handles reliably.
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 1/4 · how much data exists 3/4.
Ensuring adherence to budgets
shifting to AI
This is reading one thing and writing another: adherence in, a record out. That is the shape today's tools are built for.
importance 75 · 3551/00
Source: “Ensure adherence to budgets.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): 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: Tracking spend against budget is straightforward monitoring, though holding people to it needs a person.
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 1/4 · how much data exists 3/4.
Making arrangements or issuing instructions for shipping and delivery of materials with carrier representatives
shifting to AI
This is reading one thing and writing another: arrangements in, a record out. That is the shape today's tools are built for.
importance 75 · 3551/00
Source: “Make arrangements or issue instructions for shipping and delivery of materials with carrier representatives.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 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; mistakes that are cheap to catch.
The rating behind it: Booking shipments and issuing delivery instructions is routine admin that logistics systems already automate.
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 1/4 · how much data exists 3/4.
Managing budgets and outline costs to clients
shifting to AI
This is reading one thing and writing another: budgets in, a record out. That is the shape today's tools are built for.
importance 70 · 3551/00
Source: “Manage budgets and outline costs to clients.” (UK task statement)
How this row was scored
Exposure score: 64 out of 100 (60–68 allowing for uncertainty): 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: Budget tracking and cost breakdowns are calculation and reporting work software does well.
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 1/4 · how much data exists 3/4.
Managing stock to meet procurement and operational needs
changing shape
The software now makes the first pass at stock, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 3551/00
Source: “Manage stock to meet procurement and operational needs.” (UK task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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; mistakes that are cheap to catch.
The rating behind it: Stock levels and ordering are largely system-driven, though someone still counts what is in the fridge.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Selecting and ordering merchandise considering factors like environmental soundness
changing shape
The software now makes the first pass at merchandise considering factors like environmental soundness, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 85 · 3551/00
Source: “Select and order merchandise considering factors like environmental soundness.” (UK task statement)
How this row was scored
Exposure score: 56 out of 100 (49–63 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; mistakes that are cheap to catch.
The rating behind it: Choosing stock, including on environmental grounds, is comparison work AI does well from supplier information.
The five ratings: output a model can produce 3/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Consulting with shop managers about budgets to ensure effective financial management
changing shape
The software now makes the first pass at shop managers, 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 60 · 3551/00
Source: “Consult with shop managers about budgets to ensure effective financial management.” (UK 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; the value is that a specific person does it.
The rating behind it: Budget figures prepare themselves, but agreeing them with managers happens in conversation.
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 2/4 · how much data exists 3/4.
Negotiating deadlines for project delivery
changing shape
The software now makes the first pass at deadlines, 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 50 · 3551/00
Source: “Negotiate deadlines for project delivery.” (UK 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; the value is that a specific person does it.
The rating behind it: Deadlines are simple to propose, but agreeing one that both sides will honour is a conversation.
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 2/4 · how much data exists 3/4.
Collaborating with internal and external functions to develop product ranges
changing shape
The software now makes the first pass at internal and external functions, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 75 · 3551/00
Source: “Collaborate with internal and external functions to develop product ranges.” (UK task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: mistakes that are cheap to catch.
The rating behind it: Range development can be part drafted, though it depends on working details through with colleagues and suppliers.
The five ratings: output a model can produce 2/4 · 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 2/4.
Determining customer needs by communicating with customers
changing shape
The software now makes the first pass at customer needs, 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 60 · 3551/00
Source: “Determine customer needs by communicating with customers, sales staff, and marketing staff.” (UK task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial 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: Customer needs are written up easily, but they emerge through conversation with several groups.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Collaborating with supply chain partners to produce products meeting specific business and consumer requirements
staying human
The value here is that a specific person handles supply chain partners and stands behind it. That is earned, not computed.
importance 70 · 3551/00
Source: “Collaborate with supply chain partners to produce products meeting specific business and consumer requirements.” (UK task statement)
How this row was scored
Exposure score: 26 out of 100 (19–33 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Getting a supplier to make what you want is worked out together over time.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 2/4.
Monitoring product quality to ensure compliance with standards and specifications
staying human
This work happens in the physical world: product quality, in a real place. Software cannot follow it there.
importance 70 · 3551/00
Source: “Monitor product quality to ensure compliance with standards and specifications.” (UK task statement)
How this row was scored
Exposure score: 25 out of 100 (18–32 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch; work that happens in the physical world.
The rating behind it: Quality data can be tracked automatically, but checking that the goods themselves match the specification often means handling the product.
The five ratings: output a model can produce 2/4 · needs a body in a room 2/4 · needs an accountable person 1/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Inspecting merchandise or products to determine quality
staying human
This work happens in the physical world: merchandise, in a real place. Software cannot follow it there.
importance 70 · 3551/00
Source: “Inspect merchandise or products to determine quality, value, or yield.” (UK task statement)
How this row was scored
Exposure score: 8 out of 100 (1–15 allowing for uncertainty): minimal exposure, medium confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Judging quality or value by inspecting goods means handling and looking at the actual items.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Attending trade fairs, in the UK and overseas, to select and assemble a new collection of products
staying human
This work happens in the physical world: trade fairs, in a real place. Software cannot follow it there.
importance 80 · 3551/00
Source: “Attend trade fairs, in the UK and overseas, to select and assemble a new collection of products.” (UK task statement)
How this row was scored
Exposure score: 7 out of 100 (3–11 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world.
The rating behind it: Selecting a collection at a trade fair means seeing and handling the products in person.
The five ratings: output a model can produce 1/4 · needs a body in a room 3/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 2/4.
Attending meetings to network with peers in purchasing
staying human
This work happens in the physical world: meetings, in a real place. Software cannot follow it there.
importance 70 · 3551/00
Source: “Attend meetings to network with peers in purchasing.” (UK task statement)
How this row was scored
Exposure score: 4 out of 100 (0–8 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: work that happens in the physical world; the value is that a specific person does it.
The rating behind it: Peer networking works because people meet each other and stay in touch.
The five ratings: output a model can produce 0/4 · needs a body in a room 2/4 · needs an accountable person 0/4 · needs to be trusted in the moment 3/4 · how much data exists 2/4.
Developing and maintaining professional relationships with stakeholders and senior managers
staying human
The value here is that a specific person handles professional relationships and stands behind it. That is earned, not computed.
importance 60 · 3551/00
Source: “Develop and maintain professional relationships with stakeholders and senior managers.” (UK task statement)
How this row was scored
Exposure score: 2 out of 100 (0–6 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the value is that a specific person does it.
The rating behind it: Professional relationships with senior colleagues exist between people, and cannot be produced by anything else.
The five ratings: output a model can produce 0/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 4/4 · how much data exists 1/4.
Inspecting products to ensure they meet specifications
staying human
This work happens in the physical world: products, in a real place. Software cannot follow it there.
importance 70 · 3551/00
Source: “Inspect products to ensure they meet specifications.” (UK task statement)
How this row was scored
Exposure score: 0 out of 100 (0–4 allowing for uncertainty): minimal exposure, high confidence.
Why it sits in this group: the same decision, made over and over; work that happens in the physical world.
The rating behind it: Checking that delivered products match the specification means physically examining them.
The five ratings: output a model can produce 0/4 · needs a body in a room 4/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.

What this job pays, and how many people do it

Median pay: £37,300a year, before tax, the middle of the range, so half earn more and half earn less.ashe-t14, 2025 · ASHE 2025 provisional (reference April 2025)Provisional, because the ONS revises this figure in the autumn.
How we know this
Source: ashe-t14
Reference period: ASHE 2025 provisional (reference April 2025)
Rounding: Shown to the nearest £100. The exact published figure is in the downloadable dataset. We do not render pounds the survey cannot support.
People doing this job: 64,100in the UK, 2026.nomis-aps · Apr 2025-Mar 2026 (latest APS 12-month period)This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.

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: contract terms, conditions and obligations in, a record out. The rows above are exactly that shape: approving invoices for procurement and purchasing activities and evaluating contract terms, conditions and obligations to ensure delivery and supplier performance. What it cannot do is be there in the room, and that is still where trade fairs get done. 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: approving invoices for procurement and purchasing activities is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 53% of this job's task weight sits in rows the software is already learning, 23% in rows that change shape rather than disappear, and 25% in rows it is nowhere near. That is the position, measured across 40 scored tasks. It is not a forecast about you.

What you have that the software does not is attending trade fairs, in the UK and overseas, to select and assemble a new collection of products, 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 contract terms, conditions and obligations 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 contract terms, conditions and obligations, 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 approving invoices for procurement and purchasing activities” 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 attending trade fairs, in the UK and overseas, to select and assemble a new collection of products 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, spend an hour with National Careers Service. It is free and government-funded, 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 UK occupations to buyers and procurement officers (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was merchandisers: only about 17% of its durable work is work you already do and it pays 13.8% less. Your own job splits about 53/47: that share of the list sits in the top exposure band and the rest does not. On this evidence the honest move is inside the job rather than out of it. Become the person who owns “buy merchandise or commodities for resale to wholesale or retail consumers”, and let the exposed end go.

How that was checked: this job was compared against all 412 UK 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.

Merchandisers
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “attend trade fairs, in the UK and overseas, to select and assemble a new collection of…”. Across the whole of both lists that adds up to about 17% of the work in that job the software is not taking.
Why I am not recommending it: You would be starting most of it from nothing: about 17% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on. It is a pay cut, in those words: £32,155 against your £37,306, 13.8% less (ASHE Table 14.7a, 2025 provisional (both)). Retraining to earn less is a decision, not advice.
Look at that job’s page anyway →
Shopkeepers and owners - retail and wholesale
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “inspect merchandise or products to determine quality, value, or yield”. Across the whole of both lists that adds up to about 14% of the work in that job the software is not taking.
Why I am not recommending it: You would be starting most of it from nothing: about 14% of the durable work in that job is work you do today, and the rest you would be learning while the bills carried on.
Look at that job’s page anyway →
Purchasing managers and directors
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already negotiate orders with suppliers, and their equivalent is to negotiate contracts with customers and suppliers to secure favourable terms. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

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: 53% of its task weight, across 40 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: attending trade fairs, in the UK and overseas, to select and assemble a new collection of products 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 Kingdom figures

The United States splits this work across more than one official group, of which Buyers and Purchasing Agents is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United States page →partial match

In US official statistics this job is counted as Buyers and Purchasing Agents. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Two honest options, and no deadline on either

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.

In England:
National Careers Service
A free hour with a government-funded careers adviser is worth more than another evening of reading. In England that's the National Careers Service.
Free, government-funded
- Discover your skills and careers (the skills assessment)
In England:
National Careers Service - Find a course
Search what's actually running near you before you spend anything.
Free to search; individual courses vary
In England:
Free courses for jobs (Level 3 qualifications)
A free Level 3 qualification you already qualify for beats a paid course you don't need.
Free for eligible adults
In England:
Skills Bootcamps
Free, up to 16 weeks, and you get a job interview at the end. In England these are Skills Bootcamps - search what's running near you.
Free for eligible adults in England
- Skills Bootcamps - what they are and who can do them (DfE, Skills for Careers)
- Skills Bootcamps - JobHelp (DWP)
In Scotland:
My World of Work (Skills Development Scotland)
In Scotland it's My World of Work, from Skills Development Scotland.
Free, publicly funded
- Skills Development Scotland
In Wales:
Careers Wales
In Wales it's Careers Wales.
Free, Welsh Government-funded
In Northern Ireland:
Careers Service Northern Ireland
In Northern Ireland it's the Careers Service on nidirect.
Free, Department for the Economy-funded

A nearby route

There's no Space built for buyers and procurement officers yet.

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

What a Space actually is, in full

The closest match is Power Automate Builders, a community for non-developers building the approvals, reminders and handoffs that keep working once real people use them. It overlaps with the part of your job that is growing: the purchase-request and approval routing, and the supplier data behind it. It does not cover negotiation or category strategy. If that overlap isn't you, the free route below covers the same ground.

Try Power Automate Builders free →

7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

After the trial it is a paid community, and you get identical data either way. If the overlap above is not your job, the moves above cost nothing and stand on their own.

Noted, and thank you. We’ll email you if a Space for buyers and procurement officers launches. Nothing else.

That did not look like an email address, so nothing was saved. Have another go below.

We could not save that. The fault is ours, not yours, and your address was not stored. Please try again later.

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 Buyers and procurement officers?: Not as a job, but it is already doing parts of the work. Across the 40 official task statements scored for Buyers and procurement officers (United Kingdom, SOC 3551), 53% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 56 out of 100 (range 51–61, band: partial). 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 “Buyers and procurement officers” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Analyse sales figures and trends” (93/100, very high); “Extract data from financial records to inform purchasing decisions” (93/100, very high); “Approve invoices for procurement and purchasing activities” (88/100, 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 “Buyers and procurement officers” stay human?: About 25% 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: “Inspect products to ensure they meet specifications” (0/100, minimal); “Develop and maintain professional relationships with stakeholders and senior managers” (2/100, minimal); “Attend meetings to network with peers in purchasing” (4/100, minimal). 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 “Buyers and procurement officers” do about AI?: Start from the ledger rather than the headline: 53% of this job's weighted core work is exposed, and roughly 25% 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 Buyers and procurement officers 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 40 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

About the data on this page

Provisional, because the ONS revises this figure in the autumn.
This headcount comes from a survey, not a census, so treat it as a good estimate rather than an exact count.
The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
23 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: gaisi-indexProcessing: catalogue-bridge → ssc-relatedness-weighting → task-scoring → score-aggregation
Task weights: gaisi-index (relatedness)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: ashe-t14 (ASHE 2025 provisional (reference April 2025))nomis-aps (Apr 2025-Mar 2026 (latest APS 12-month period))

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.

How we score a job Download this release Look up another job

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}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. 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.