Purchasing Managers
In short: today's best AI models could do about 46% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 77% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 23% of the time, stays with people.
Plan, direct, or coordinate the activities of buyers, purchasing officers, and related workers involved in purchasing materials, products, and services. Includes wholesale or retail trade merchandising managers and procurement managers.
84,320 people do this job in the US. $148,080 a year.
Reviewed on October 1, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on1 h
- A person checks AI's work18 h
- Desk work AI can't do yet12 h
- Stays with people9 h
Purchasing Managers, now: of a 40-hour week, AI could take on 1 hours, 18 hours become checking its work, 12 hours are desk work it can't do yet, and 9 hours stay with people.
The largest pieces: Develop savings plans (about 2 h, a person checks); Analyze supply markets (about 2 h, a person checks); Set purchasing policies (about 2 h, a person checks).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 68%
- 9%
- 23%
- 0%
- 0%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
What handing it over would take, now
The 46% within reach splits by what a model would need. The dates, pace and reliability follow the controls above. Estimates.
of the working time. The material can be handed to a model and the result handed back.
of the working time. The model has to be connected to the system the work lives in.
is conversation short enough by length. This site leaves conversation with people, so it is not in the total.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 12%. Today's estimate: 46%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.021% went to this job's tasks in May 2026, the 324th largest of the 447 jobs that showed up at all; 1 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.034% to 0.031% (released February and March 2025); 0.032% to 0.06% (August 2025 to February 2026); 0.023% to 0.021% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.034% | 343 of 708 | 5 of 18 |
| Released March 2025 | 0.031% | 351 of 703 | 4 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.032% | 297 of 655 | 5 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.041% | 269 of 672 | 6 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.06% | 228 of 677 | 6 of 18 |
| April 2026 (released June 2026) | 0.023% | 317 of 434 | 1 of 18 |
| May 2026 (released June 2026) | 0.021% | 324 of 447 | 1 of 18 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates almost none of this job's working time as physical work, so robots do not reach it.
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
What changes for the people in this job
From the task-by-task review, by the end of 2028 on the long-run pace at four in five. It says which parts of the work stay with people and which change, not whether anyone keeps a job: that depends on decisions no data set can see.
What stays with people
22% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Negotiate supplier contracts, the conversation, 7%
- Direct purchasing staff, the conversation, 5%
- Find and interview vendors, the conversation, 4%
- Set purchasing policies, the conversation, 4%
- Help develop specifications, the conversation, 1%
- Hire and train staff, the conversation, 0.6%
What becomes checking the machine
74% of the working time: desk work a model could do by then, in tasks where a mistake costs something or a licensed person signs. A person checks it. Another 2% is desk work that is small if wrong, which can be handed over with lighter checks.
- Develop savings plans, costly if wrong, 19%
- Set purchasing policies, costly if wrong, 15%
- Analyze supply markets, costly if wrong, 9%
- Report on markets and costs, costly if wrong, 4%
- Administer purchasing systems, costly if wrong, 4%
- Direct purchasing staff, costly if wrong, 4%
What to learn
- Reviewing work you did not do yourself. The tasks under What becomes checking the machine, where a mistake costs something, stay a person's to check: spotting what a draft gets wrong is a skill of its own.
- Briefing a model and checking its drafts. About 68% of the time is documents and data, the part models reach first: writing a clear brief, giving the right material, and checking what comes back.
- The conversations. About 23% of the time is conversation and in-person work, which this site leaves with people: listening, explaining, persuading, calming.
- Dealing with people outside the organization. Customers, patients, suppliers or the public: trust with them is built by a person.
Your own version of this job: read it against your job description. The headline is free; the full personal report, every task with its timeline and what to learn, is $19 (a sample).
The tasks
Sorted by . 18 tasks from .
| Task | ||||
|---|---|---|---|---|
| Develop and implement purchasing and contract management instructions, policies, and procedures.Writing the policies and rolling them out.Done more than yearly by most who do it. | 19% | 1.7 work days3.3 h to 4.2 work days | Documents 80%, conversation 20% | 25%Desk part half by Mar 2027 |
| Develop cost reduction strategies and savings plans.Analysis and the plan written up.Done more than yearly by most who do it. | 19% | 1.7 work days3.3 h to 4.2 work days | Documents 100% | 31%Half by Mar 2027 |
| Represent companies in negotiating contracts and formulating policies with suppliers.Negotiations with suppliers, with the contract drafted.Done more than monthly by most who do it. | 10% | 6.7 h1.7 h to 2.1 work days | Conversation 70%, documents 30% | 18%Desk part half by now |
| Analyze market and delivery systems to assess present and future material availability.Market analysis.Done more than monthly by most who do it. | 9% | 6.7 h1.7 h to 2.1 work days | Documents 100% | 61%Half by now |
| Direct and coordinate activities of personnel engaged in buying, selling, and distributing materials, equipment, machinery, and supplies.Mostly conversation with the buyers, plus reading and deciding.Done daily by most who do it. | 9% | 1.7 h25 min to 5 h | Conversation 60%, documents 40% | 38%Desk part half by now |
| Locate vendors of materials, equipment or supplies, and interview them to determine product availability and terms of sales.Research to find vendors, then calls on availability and terms.Done more than weekly by most who do it. AI observed on this task. | 7% | 3.3 h50 min to 1.3 work days | Conversation 60%, documents 40% | 32%Desk part half by now |
| Prepare reports regarding market conditions and merchandise costs.Writing the report.Done more than yearly by most who do it. AI observed on this task. | 4% | 6.7 h1.7 h to 1.7 work days | Documents 100% | 69%Half by now |
| Administer online purchasing systems.Setting up and maintaining the online purchasing system.Done more than monthly by most who do it. AI observed on this task. | 4% | 1.3 h25 min to 4.2 h | Systems 100% | 98%Half by now |
| Control purchasing department budgets.Tracking spending against the budget.Done more than yearly by most who do it. | 3% | 3.3 h1.7 h to 1.3 work days | Documents 70%, systems 30% | 97%Half by now |
| Review, evaluate, and approve specifications for issuing and awarding bids.Reading and signing off the specifications.Done more than weekly by most who do it. AI observed on this task. | 3% | 2.5 h1.3 h to 5 h | Documents 100% | 100%Half by now |
| Participate in the development of specifications for equipment, products, or substitute materials.Meetings with engineers and users, and the specification written.Done more than monthly by most who do it. | 3% | 3.3 h1.7 h to 6.7 h | Documents 60%, conversation 40% | 60%Desk part half by now |
| Review purchase order claims and contracts for conformance to company policy.Reading the contracts and claims against the policy.Done more than monthly by most who do it. | 2% | 1.7 h25 min to 3.3 h | Documents 100% | 99%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach. Made of: how the task's time splits among five kinds of doing. Only the documents and systems parts can count as within reach, so a task that is 30% documents can be at most 30% within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Procurement Clerks72% now, 72% by 2028
- Purchasing Agents, Except Wholesale, Retail, and Farm Products65% now, 79% by 2028
- Wholesale and Retail Buyers, Except Farm Products60% now, 62% by 2028
- Logistics Analysts84% now, 99% by 2028
- Logisticians38% now, 76% by 2028
- Supply Chain Managers40% now, 95% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Purchasing Managers is within reach of AI now?
- An estimated 46% of the working time is within reach of AI models now and 77% by the end of 2028, on METR's long-run pace at four in five (73% to 77% across the three paces the site shows). Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Purchasing Managers come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Develop savings plans (31% of the task's time now, 100% by the end of 2028); Analyze supply markets (61% of the task's time now, 100% by the end of 2028); and Set purchasing policies (25% of the task's time now, 80% by the end of 2028).
- Which tasks of Purchasing Managers stay with people?
- Every task has a desk part, so each can come partly within reach; the conversation, in-person and hands-on parts of each task stay with people, about 23% of the working time.
- What should Purchasing Managers learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are reviewing work you did not do yourself; briefing a model and checking its drafts; and the conversations. By the end of 2028 on the long-run pace at four in five, about 22% of the working time stays with people, 74% becomes checking a model's work and 2% could be handed over with lighter checks. It says which parts of the work change, never whether anyone keeps a job.
- Do people already use AI for the work of Purchasing Managers?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.021% went to this job's tasks, the 324th largest share of the 447 jobs that showed up; 1 of its 18 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 20%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Purchasing Managers?
- Anthropic's robot exposure rating (September 2026) finds almost none of the working time is physical work, so robots do not reach it.
- How is this estimated?
- From the 18 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, reviewed one task at a time on October 1, 2026 for what each is made of (documents, business systems, conversation, in person, hands-on), and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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