Camera Operators, Television, Video, and Film
In short: today's best AI models could do about 27% 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 32% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 68% of the time, stays with people.
Operate television, video, or film camera to record images or scenes for television, video, or film productions.
21,550 people do this job in the US. $74,990 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on11 h
- A person checks AI's work0 h
- Desk work AI can't do yet2 h
- Stays with people27 h
Camera Operators, Television, Video, and Film, now: of a 40-hour week, AI could take on 11 hours, 0 hours become checking its work, 2 hours are desk work it can't do yet, and 27 hours stay with people.
The largest pieces: Edit video for broadcast productions, including non-linear editing (about 8 h); View films to resolve problems of exposure control, subject and camera movement, changes in subject distance, and related variables (about 1 h); Read and analyze work orders and specifications to determine locations of subject material, work procedures, sequences of operations, and machine setups (under an hour).
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.
- 32%
- 14%
- 54%
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.
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, 9%. Today's estimate: 27%.
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, 0.032% went to this job's tasks in May 2026, the 259th largest of the 447 jobs that showed up at all; 1 of its 21 tasks showed up. Within each of Anthropic's methods, never across a change: 0.0066% to 0.0037% (released February and March 2025); 0.0058% to 0.026% (August 2025 to February 2026); 0.023% to 0.032% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.0066% | 577 of 708 | 2 of 21 |
| Released March 2025 | 0.0037% | 612 of 703 | 1 of 21 |
| The week of Aug 4, 2025 (released September 2025) | 0.0058% | 516 of 655 | 1 of 21 |
| The week of Nov 13, 2025 (released January 2026) | 0.02% | 386 of 672 | 4 of 21 |
| The week of Feb 5, 2026 (released March 2026) | 0.026% | 361 of 677 | 4 of 21 |
| April 2026 (released June 2026) | 0.023% | 292 of 434 | 1 of 21 |
| May 2026 (released June 2026) | 0.032% | 259 of 447 | 1 of 21 |
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 74% of this job's working time as physical work. For 31% of the working time, a robot has been shown doing most of the task somewhere: 9% in a purpose-built cell, 22% in a structured facility. 0.53 of 3, the 301st highest of the 923 jobs.
- Not physical 26%
- No robot shown 43%
- In a purpose-built cell 9%
- In a structured facility 22%
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.
The tasks
Sorted by . 21 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Edit video for broadcast productions, including non-linear editing.Done several times a day by most who do it. AI observed on this task. | 25% | 3.3 h50 min to 1.3 work days | 80%Half by now | |
| Operate television or motion picture cameras to record scenes for television broadcasts, advertising, or motion pictures.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 11% | 1.3 h25 min to 3.3 h | Stays with people | |
| Use cameras in any of several different camera mounts, such as stationary, track-mounted, or crane-mounted.Done more than weekly by most who do it. Robots: in a structured facility, Shotoku AutoFrame (TR-XT robotic control) / Telemetrics reFrame / Ross Vision[Ai]ry (deployed). Anthropic's rating. | 8% | 1.1 h25 min to 2.5 h | Stays with people | |
| Direct studio productions.Done more than monthly by most who do it. | 7% | 3.3 h50 min to 1.7 work days | Stays with people | |
| Assemble studio sets and select and arrange cameras, film stock, audio, or lighting equipment to be used during filming.Done more than monthly by most who do it.Robots: no robot shown. Anthropic's rating. | 7% | 1.7 h38 min to 3.3 h | Stays with people | |
| Compose and frame each shot, applying the technical aspects of light, lenses, film, filters, and camera settings to achieve the effects sought by directors.Done daily by most who do it. AI observed on this task.Robots: no robot shown. Anthropic's rating. | 5% | 38 min13 min to 1.7 h | Stays with people | |
| Set up and operate electric news gathering (ENG) microwave vehicles to gather and edit raw footage on location to send to television affiliates for broadcast.Done more than weekly by most who do it.Robots: no robot shown. Anthropic's rating. | 5% | 2.1 h50 min to 4.2 h | Stays with people | |
| Set up and perform live shots for broadcast.Done more than weekly by most who do it. Robots: in a structured facility, MRMC StudioBot XL robotic camera arm (Mark Roberts Motion Control) (deployed). Anthropic's rating. | 4% | 50 min25 min to 1.7 h | Stays with people | |
| Confer with directors, sound and lighting technicians, electricians, and other crew members to discuss assignments and determine filming sequences, desired effects, camera movements, and lighting requirements.Done several times a day by most who do it. | 4% | 38 min13 min to 1.3 h | Stays with people | |
| Set up cameras, optical printers, and related equipment to produce photographs and special effects.Done more than yearly by most who do it.Robots: in a purpose-built cell, Ross Video Furio / Furio+ (deployed). Anthropic's rating. | 4% | 1.7 h38 min to 3.3 h | Stays with people | |
| Test, clean, maintain, and repair broadcast equipment, including testing microphones, to ensure proper working condition.Done daily by most who do it. Robots: in a purpose-built cell, IQLaR (Imatest / Sofica) (sold). Anthropic's rating. | 4% | 50 min17 min to 1.7 h | Stays with people | |
| Observe sets or locations for potential problems and to determine filming and lighting requirements.Done more than monthly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 38 min13 min to 1.7 h | 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.
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.
- Electro-Mechanical and Mechatronics Technologists and Technicians20% now, 26% by 2028
- Broadcast Technicians31% now, 32% by 2028
- Audio and Video Technicians48% now, 56% by 2028
- Media Technical Directors/Managers38% now, 38% by 2028
- Avionics Technicians13% now, 15% by 2028
- Camera and Photographic Equipment Repairers7% now, 7% 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 Camera Operators, Television, Video, and Film is within reach of AI now?
- An estimated 27% of the working time is within reach of AI models now and 32% 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 Camera Operators, Television, Video, and Film 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: Edit video for broadcast productions, including non-linear editing (80% of the task's time now, 100% by the end of 2028); View films to resolve problems of exposure control, subject and camera movement, changes in subject distance, and related variables (100% of the task's time now); and Read and analyze work orders and specifications to determine locations of subject material, work procedures, sequences of operations, and machine setups (100% of the task's time now).
- Which tasks of Camera Operators, Television, Video, and Film stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Operate television or motion picture cameras to record scenes for television broadcasts, advertising, or motion pictures; Use cameras in any of several different camera mounts, such as stationary, track-mounted, or crane-mounted; and Direct studio productions. Together such tasks are about 68% of the working time.
- Do people already use AI for the work of Camera Operators, Television, Video, and Film?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.032% went to this job's tasks, the 259th largest share of the 447 jobs that showed up; 1 of its 21 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 17%. 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 Camera Operators, Television, Video, and Film?
- Anthropic's robot exposure rating (September 2026) finds 74% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 31% of the working time, 22% in a structured facility. Its index is 0.53 of 3. One example: Shotoku AutoFrame (TR-XT robotic control) / Telemetrics reFrame / Ross Vision[Ai]ry for "use cameras in any of several different camera mounts, such as stationary, track-mounted, or crane-mounted". 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 21 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, 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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