Reservation and Transportation Ticket Agents and Travel Clerks
In short: today's best AI models could do about 36% 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 64% of the time, stays with people.
Make and confirm reservations for transportation or lodging, or sell transportation tickets. May check baggage and direct passengers to designated concourse, pier, or track; deliver tickets and contact individuals and groups to inform them of package tours; or provide tourists with travel or transportation information.
118,710 people do this job in the US. $44,390 a year.
Reviewed on September 30, 2026: what each task is made of, and what handing it over would ask.
A typical 40-hour week
- AI could take on3 h
- A person checks AI's work12 h
- Desk work AI can't do yet0 h
- Stays with people25 h
Reservation and Transportation Ticket Agents and Travel Clerks, now: of a 40-hour week, AI could take on 3 hours, 12 hours become checking its work, 0 hours are desk work it can't do yet, and 25 hours stay with people.
The largest pieces: Make and confirm reservations (about 4 h, a person checks); Plan itineraries and compute fares (about 3 h, a person checks); Invoice and take payment (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.
- 8%
- 29%
- 24%
- 25%
- 14%
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 36% 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, 5%. With Claude Mythos Preview (early), measured in April 2026, 36%. Today's estimate: 36%.
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, 0.064% went to this job's tasks in May 2026, the 216th largest of the 447 jobs that showed up at all; 1 of its 19 tasks showed up. Within each of Anthropic's methods, never across a change: 0.094% to 0.12% (released February and March 2025); 0.25% to 0.47% (August 2025 to February 2026); 0.068% to 0.064% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.094% | 173 of 708 | 6 of 19 |
| Released March 2025 | 0.12% | 141 of 703 | 6 of 19 |
| The week of Aug 4, 2025 (released September 2025) | 0.25% | 72 of 655 | 7 of 19 |
| The week of Nov 13, 2025 (released January 2026) | 0.21% | 82 of 672 | 8 of 19 |
| The week of Feb 5, 2026 (released March 2026) | 0.47% | 42 of 677 | 7 of 19 |
| April 2026 (released June 2026) | 0.068% | 208 of 434 | 1 of 19 |
| May 2026 (released June 2026) | 0.064% | 216 of 447 | 1 of 19 |
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 17% of this job's working time as physical work. For 13% of the working time, a robot has been shown doing most of the task somewhere: 3% in a purpose-built cell, 10% in a structured facility. 0.23 of 3, the 415th highest of the 923 jobs.
- Not physical 83%
- No robot shown 4%
- In a purpose-built cell 3%
- In a structured facility 10%
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
64% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Learn customers' travel preferences, the conversation, 12%
- Keep the counter clean, the hands-on work, 7%
- Promote destinations and packages, the conversation, 6%
- Make and confirm reservations, the conversation, 6%
- Invoice and take payment, the in-person work, 5%
- Help clients with travel documents, the in-person work, 5%
What becomes checking the machine
30% 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 6% is desk work that is small if wrong, which can be handed over with lighter checks.
- Make and confirm reservations, costly if wrong, 9%
- Plan itineraries and compute fares, costly if wrong, 8%
- Invoice and take payment, costly if wrong, 5%
- Help clients with travel documents, costly if wrong, 3%
- Issue tickets and itineraries, costly if wrong, 3%
- Check documents and issue boarding passes, costly if wrong, 0.7%
What to learn
- The conversations. About 49% 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.
- Running AI inside the business systems. About 29% of the time is work inside business systems, which a model can do only once it is connected: knowing the systems well enough to set that up and watch it.
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 . 19 tasks from .
| Task | ||||
|---|---|---|---|---|
| Make and confirm reservations for transportation and accommodations, using telephones, faxes, mail, and computers.Bookings in the system, with calls.Done hourly or more by most who do it. AI observed on this task. | 15% | 21 min8 min to 38 min | Systems 60%, conversation 40% | 60%Desk part half by now |
| Confer with customers to determine their service requirements and travel preferences.Conversations at the counter and by phone.Done hourly or more by most who do it. AI observed on this task. | 12% | 17 min8 min to 29 min | Conversation 50%, in person 50% | Stays with people |
| Prepare customer invoices and accept payment.The invoice prepared and payment taken at the counter.Done hourly or more by most who do it. | 11% | 13 min8 min to 21 min | Systems 50%, in person 30%, hands-on 20% | 50%Desk part half by now |
| Provide clients with assistance in preparing required travel documents and forms.Helping the client with forms at the counter.Done hourly or more by most who do it. | 9% | 25 min13 min to 42 min | In person 60%, documents 40% | 40%Desk part half by now |
| Plan routes, itineraries, and accommodation details, and compute fares and fees, using schedules, rate books, and computers.Routes and fares worked out with schedules and the system.Done hourly or more by most who do it. AI observed on this task. | 8% | 25 min13 min to 50 min | Documents 50%, systems 50% | 100%Half by now |
| Keep information facilities clean during operation.Tidying the facility.Done hourly or more by most who do it.Robots: in a purpose-built cell, Avidbots Neo (deployed). Anthropic's rating. | 7% | 13 min4 min to 25 min | Hands-on 100% | Stays with people |
| Promote particular destinations, tour packages, and other travel services.Selling packages in conversation.Done hourly or more by most who do it. | 6% | 17 min8 min to 33 min | Conversation 50%, in person 50% | Stays with people |
| Determine whether space is available on travel dates requested by customers, assigning requested spaces when available.Availability looked up and space assigned, with the customer on the line.Done daily by most who do it. | 5% | 10 min4 min to 17 min | Systems 70%, conversation 30% | 70%Desk part half by now |
| Inform clients of essential travel information, such as travel times, transportation connections, or medical and visa requirements.Times, connections and visa requirements explained.Done hourly or more by most who do it. | 5% | 13 min7 min to 25 min | Conversation 50%, in person 50% | Stays with people |
| Assemble and issue required documentation, such as tickets, travel insurance policies, or itineraries.Documents produced in the system and handed over.Done daily by most who do it. | 4% | 17 min8 min to 29 min | Systems 70%, hands-on 30% | 70%Desk part half by now |
| Answer inquiries regarding information, such as schedules, accommodations, procedures, or policies.Questions at the counter and by phone.Done hourly or more by most who do it. | 3% | 7 min3 min to 13 min | Conversation 50%, in person 50% | Stays with people |
| Provide boarding or disembarking assistance to passengers needing special assistance.Helping passengers who need assistance.Done hourly or more by most who do it.Robots: no robot shown. Anthropic's rating. | 3% | 17 min8 min to 38 min | Hands-on 60%, in person 40% | Stays with people |
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 Reservation and Transportation Ticket Agents and Travel Clerks is within reach of AI now?
- An estimated 36% of the working time is within reach of AI models now and 36% 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 Reservation and Transportation Ticket Agents and Travel Clerks 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: Make and confirm reservations (60% of the task's time now); Plan itineraries and compute fares (100% of the task's time now); and Invoice and take payment (50% of the task's time now).
- Which tasks of Reservation and Transportation Ticket Agents and Travel Clerks stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Learn customers' travel preferences; Keep the counter clean; and Promote destinations and packages. Together such tasks are about 40% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Reservation and Transportation Ticket Agents and Travel Clerks learn as AI takes on more of the work?
- By the job's own task-by-task review, the first things to learn are the conversations; dealing with people outside the organization; and reviewing work you did not do yourself. By the end of 2028 on the long-run pace at four in five, about 64% of the working time stays with people, 30% becomes checking a model's work and 6% 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 Reservation and Transportation Ticket Agents and Travel Clerks?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.064% went to this job's tasks, the 216th largest share of the 447 jobs that showed up; 1 of its 19 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 25%. 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 Reservation and Transportation Ticket Agents and Travel Clerks?
- Anthropic's robot exposure rating (September 2026) finds 17% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 13% of the working time, 10% in a structured facility. Its index is 0.23 of 3. One example: Avidbots Neo for "keep the counter clean". 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 19 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 September 30, 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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