Database Administrators
In short: today's best AI models could do about 68% 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 88% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 12% of the time, stays with people.
Administer, test, and implement computer databases, applying knowledge of database management systems. Coordinate changes to computer databases. Identify, investigate, and resolve database performance issues, database capacity, and database scalability. May plan, coordinate, and implement security measures to safeguard computer databases.
69,990 people do this job in the US. $104,620 a year.
Reviewed on October 2, 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 work26 h
- Desk work AI can't do yet8 h
- Stays with people5 h
Database Administrators, now: of a 40-hour week, AI could take on 1 hours, 26 hours become checking its work, 8 hours are desk work it can't do yet, and 5 hours stay with people.
The largest pieces: Test and fix programs and databases (about 6 h, a person checks); Recommend database technologies (about 3 h, a person checks); Change databases or direct changes (about 3 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.
- 61%
- 26%
- 11%
- 1%
- 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 68% 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: 68%.
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, 0.12% went to this job's tasks in May 2026, the 146th largest of the 447 jobs that showed up at all; 4 of its 18 tasks showed up. Within each of Anthropic's methods, never across a change: 0.99% to 0.72% (released February and March 2025); 0.65% to 0.6% (August 2025 to February 2026); 0.14% to 0.12% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 0.99% | 18 of 708 | 12 of 18 |
| Released March 2025 | 0.72% | 27 of 703 | 13 of 18 |
| The week of Aug 4, 2025 (released September 2025) | 0.65% | 31 of 655 | 14 of 18 |
| The week of Nov 13, 2025 (released January 2026) | 0.69% | 26 of 672 | 15 of 18 |
| The week of Feb 5, 2026 (released March 2026) | 0.6% | 32 of 677 | 13 of 18 |
| April 2026 (released June 2026) | 0.14% | 135 of 434 | 5 of 18 |
| May 2026 (released June 2026) | 0.12% | 146 of 447 | 4 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
12% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Train users and answer questions, the conversation, 4%
- Plan and oversee installations, the conversation, 3%
- Support staff and clients, the conversation, 3%
- Change databases or direct changes, the conversation, 2%
What becomes checking the machine
84% 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 3% is desk work that is small if wrong, which can be handed over with lighter checks.
- Recommend database technologies, costly if wrong, 16%
- Test and fix programs and databases, costly if wrong, 15%
- Develop data models, costly if wrong, 8%
- Code database descriptions, costly if wrong, 8%
- Change databases or direct changes, costly if wrong, 8%
- Test database changes, costly if wrong, 7%
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 61% 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.
- Running AI inside the business systems. About 26% 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 . 18 tasks from .
| Task | ||||
|---|---|---|---|---|
| Identify, evaluate and recommend hardware or software technologies to achieve desired database performance.Comparing hardware and software options and writing the recommendation.Done more than yearly by most who do it. AI observed on this task. | 16% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%Half by now |
| Test programs or databases, correct errors, and make necessary modifications.Running tests, fixing the code and applying the changes.Done daily by most who do it. AI observed on this task. | 15% | 4.2 h1.7 h to 1.3 work days | Documents 50%, systems 50% | 93%Half by now |
| Modify existing databases and database management systems or direct programmers and analysts to make changes.Writing and applying changes to the databases, or handing them to programmers and checking.Done more than monthly by most who do it. AI observed on this task. | 9% | 2.5 h50 min to 6.7 h | Documents 40%, systems 40%, conversation 20% | 77%Desk part half by now |
| Approve, schedule, plan, and supervise the installation and testing of new products and improvements to computer systems, such as the installation of new databases.Planning and scheduling each installation and keeping the team to it.Done more than monthly by most who do it. | 8% | 1 work day3.3 h to 4.2 work days | Documents 40%, conversation 40%, systems 20% | 31%Desk part half by now |
| Develop data models describing data elements and how they are used, following procedures and using pen, template, or computer software.Drawing and documenting how the data items relate.Done more than yearly by most who do it. | 8% | 5 h1.7 h to 2.5 work days | Documents 100% | 67%Half by now |
| Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.Writing the schema definitions and loading them into the management system.Done more than weekly by most who do it. | 8% | 4.2 h1.7 h to 1.7 work days | Documents 80%, systems 20% | 86%Half by now |
| Test changes to database applications or systems.Running the changed applications against the database and checking the results.Done more than monthly by most who do it. | 7% | 3.3 h50 min to 1 work day | Systems 60%, documents 40% | 86%Half by now |
| Train users and answer questions.Showing users how the database works and answering what comes up.Done daily by most who do it. | 4% | 1.3 h25 min to 3.3 h | Conversation 80%, in person 20% | Stays with people |
| Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.Deciding the safeguards and configuring them in the systems.Done more than monthly by most who do it. | 4% | 4.2 h1.7 h to 2.1 work days | Documents 50%, systems 50% | 79%Half by now |
| Provide technical support to junior staff or clients.Answering questions and fixing problems by call, chat and email.Done daily by most who do it. AI observed on this task. | 4% | 50 min17 min to 2.5 h | Conversation 70%, documents 30% | 30%Desk part half by now |
| Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.Writing the rules for choosing software and protecting sensitive data.Done more than yearly by most who do it. | 3% | 6.7 h2.5 h to 2.5 work days | Documents 100% | 69%Half by now |
| Identify and evaluate industry trends in database systems to serve as a source of information and advice for upper management.Reading about where database technology is going and advising management in writing.Done more than yearly by most who do it. | 3% | 5 h1.7 h to 2.1 work days | Documents 100% | 73%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 Database Administrators is within reach of AI now?
- An estimated 68% of the working time is within reach of AI models now and 88% by the end of 2028, on METR's long-run pace at four in five (86% to 88% 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 Database Administrators 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: Test and fix programs and databases (93% of the task's time now, 100% by the end of 2028); Recommend database technologies (55% of the task's time now, 100% by the end of 2028); and Change databases or direct changes (77% of the task's time now).
- Which tasks of Database Administrators stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Train users and answer questions. Together such tasks are about 4% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Database Administrators 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 running AI inside the business systems. By the end of 2028 on the long-run pace at four in five, about 12% of the working time stays with people, 84% becomes checking a model's work and 3% 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 Database Administrators?
- In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.12% went to this job's tasks, the 146th largest share of the 447 jobs that showed up; 4 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 33%. 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 Database Administrators?
- 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 2, 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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