Transportation Security Screeners
In short: today's best AI models could do about 11% 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 the same by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 89% of the time, stays with people.
Conduct screening of passengers, baggage, or cargo to ensure compliance with Transportation Security Administration (TSA) regulations. May operate basic security equipment such as x-ray machines and hand wands at screening checkpoints.
50,290 people do this job in the US. $66,770 a year.
Reviewed on October 19, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on0 h
- A person checks AI's work4 h
- Desk work AI can't do yet0 h
- Stays with people36 h
Transportation Security Screeners, now: of a 40-hour week, AI could take on 0 hours, 4 hours become checking its work, 0 hours are desk work it can't do yet, and 36 hours stay with people.
The largest pieces: Log alarmed baggage (about 1 h, a person checks); Read x-ray images of carry-on bags (about 1 h, a person checks); Screen bag images remotely (under an hour, 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.
- 0%
- 11%
- 2%
- 29%
- 58%
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 11% 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, 9%. With Claude Mythos Preview (early), measured in April 2026, 11%. Today's estimate: 11%.
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, no reportable share went to this job's tasks in May 2026; 0 of its 26 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0041% to 0.0064% (released February and March 2025); 0.0067% to 0.0081% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0041% | 633 of 708 | 1 of 26 |
| Released March 2025 | 0.0064% | 560 of 703 | 1 of 26 |
| The week of Aug 4, 2025 (released September 2025) | 0.0067% | 505 of 655 | 1 of 26 |
| The week of Nov 13, 2025 (released January 2026) | 0.0052% | 572 of 672 | 1 of 26 |
| The week of Feb 5, 2026 (released March 2026) | 0.0081% | 524 of 677 | 2 of 26 |
| April 2026 (released June 2026) | none | n/a | 0 of 26 |
| May 2026 (released June 2026) | none | n/a | 0 of 26 |
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 46% of this job's working time as physical work. For 24% of the working time, a robot has been shown doing most of the task somewhere: 7% in a purpose-built cell, 17% in a structured facility. 0.41 of 3, the 340th highest of the 923 jobs.
- Not physical 54%
- No robot shown 22%
- In a purpose-built cell 7%
- In a structured facility 17%
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
88% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Keep the checkpoint moving, the in-person work, 22%
- Search bags by hand, the hands-on work, 11%
- Patrol for suspicious items, the hands-on work, 9%
- Pat down or wand passengers, the hands-on work, 8%
- Swab bags for explosives, the hands-on work, 6%
- Confiscate dangerous items, the hands-on work, 4%
What becomes checking the machine
11% 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.
- Log alarmed baggage, costly if wrong, 3%
- Read x-ray images of carry-on bags, severe if wrong, 3%
- Screen bag images remotely, severe if wrong, 2%
- Decide on alarmed bags, severe if wrong, 2%
What to learn
- Judgment where errors are severe. Some tasks are severe if wrong. Knowing when not to trust an output matters more there than speed.
- The hands-on craft. About 58% of the time is hands-on work, which no model here does; robots are rated separately on this page.
- The conversations. About 31% 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.
- 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.
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 . 26 tasks from .
| Task | ||||
|---|---|---|---|---|
| Monitor passenger flow through screening checkpoints to ensure order and efficiency.Watching the lines and directing passengers to keep order.Done hourly or more by most who do it. | 22% | 25 min13 min to 50 min | In person 60%, hands-on 40% | Stays with people |
| Search carry-on or checked baggage by hand when it is suspected to contain prohibited items such as weapons.Going through the bag by hand.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 13 min4 min to 38 min | Hands-on 100% | Stays with people |
| Patrol work areas to detect any suspicious items.Walking the area and looking.Done daily by most who do it. Robots: in a structured facility, SPF airport patrol robot (Terminal 4) (Singapore Police Force / HTX) (deployed). Anthropic's rating. | 9% | 17 min8 min to 38 min | Hands-on 100% | Stays with people |
| Perform pat-down or hand-held wand searches of passengers who have triggered machine alarms, who are unable to pass through metal detectors, or who have been randomly identified for such searches.The search by hand, with the passenger told what is being done.Done hourly or more by most who do it. Robots: no robot shown. Anthropic's rating. | 8% | 7 min3 min to 17 min | Hands-on 70%, in person 30% | Stays with people |
| Test baggage for any explosive materials, using equipment such as explosive detection machines or chemical swab systems.Swabbing and running the trace machine.Done hourly or more by most who do it. Robots: in a purpose-built cell, In-line Explosives Detection Systems (CT-based EDS) in checked baggage handling systems (TSA / EDS vendors) (deployed). Anthropic's rating. | 6% | 4 min2 min to 13 min | Hands-on 100% | Stays with people |
| Decide whether baggage that triggers alarms should be searched or should be allowed to pass through.Judging from the image and the bag whether it needs a search.Done hourly or more by most who do it. | 4% | 4 min2 min to 17 min | Systems 50%, hands-on 50% | 50%Desk part half by now |
| Confiscate dangerous items and hazardous materials found in opened bags and turn them over to airlines for disposal.Taking the item from the bag and handing it to the airline.Done several times a day by most who do it. Robots: no robot shown. Anthropic's rating. | 4% | 8 min4 min to 21 min | Hands-on 100% | Stays with people |
| Inspect checked baggage for signs of tampering.Looking the bags over by hand.Done hourly or more by most who do it. Robots: in a structured facility, VISY ADDS 2.0 (Automatic Damage Detection System) (deployed). Anthropic's rating. | 3% | 3 min1 min to 8 min | Hands-on 100% | Stays with people |
| Send checked baggage through automated screening machines, and set bags aside for searching or rescreening as indicated by equipment.Loading bags into the machine and pulling the ones it flags.Done hourly or more by most who do it. Robots: in a structured facility, Checked Baggage Inspection System (CBIS) with integrated EDS, Missoula International Airport (TSA / baggage handling system integrators) (deployed). Anthropic's rating. | 3% | 3 min1 min to 8 min | Hands-on 100% | Stays with people |
| Record information about any baggage that sets off alarms in monitoring equipment.Entries in the log for each alarm.Done hourly or more by most who do it. | 3% | 4 min2 min to 8 min | Systems 100% | 100%Half by now |
| Inspect carry-on items, using x-ray viewing equipment, to determine whether items contain objects that warrant further investigation.Watching the x-ray screen for items that need a closer look.Done hourly or more by most who do it. | 3% | 3 min1 min to 8 min | Systems 100% | 100%Half by now |
| View images of checked bags and cargo, using remote screening equipment, and alert baggage screeners or handlers to any possible problems.Watching the images at the console and radioing the handlers about problems.Done hourly or more by most who do it. | 3% | 3 min1 min to 8 min | Systems 80%, conversation 20% | 80%Desk part 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.
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 Transportation Security Screeners is within reach of AI now?
- An estimated 11% of the working time is within reach of AI models now and 11% by the end of 2028, on METR's long-run pace at four in five. 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 Transportation Security Screeners 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: Log alarmed baggage (100% of the task's time now); Read x-ray images of carry-on bags (100% of the task's time now); and Screen bag images remotely (80% of the task's time now).
- Which tasks of Transportation Security Screeners stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Keep the checkpoint moving; Search bags by hand; and Patrol for suspicious items. Together such tasks are about 86% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Transportation Security Screeners learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are judgment where errors are severe; the hands-on craft; and the conversations. By the end of 2028 on the long-run pace at four in five, about 88% of the working time stays with people, 11% becomes checking a model's work and 0% 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 Transportation Security Screeners?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. 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 Transportation Security Screeners?
- Anthropic's robot exposure rating (September 2026) finds 46% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 24% of the working time, 17% in a structured facility. Its index is 0.41 of 3. One example: SPF airport patrol robot (Terminal 4) for "patrol for suspicious items". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 26 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 19, 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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