Database Architects
In short: today's best AI models could do about 28% 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 89% by the end of 2028 if progress keeps its long-run pace. The conversations, in-person and hands-on work, about 6% of the time, stays with people.
Design strategies for enterprise databases, data warehouse systems, and multidimensional networks. Set standards for database operations, programming, query processes, and security. Model, design, and construct large relational databases or data warehouses. Create and optimize data models for warehouse infrastructure and workflow. Integrate new systems with existing warehouse structure and refine system performance and functionality.
67,140 people do this job in the US. $139,500 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 work11 h
- Desk work AI can't do yet26 h
- Stays with people2 h
Database Architects, now: of a 40-hour week, AI could take on 1 hours, 11 hours become checking its work, 26 hours are desk work it can't do yet, and 2 hours stay with people.
The largest pieces: Develop data models (about 1 h, a person checks); Code database descriptions (about 1 h, a person checks); Model application data structures (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.
- 85%
- 9%
- 6%
- 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 28% 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, 3%. Today's estimate: 28%.
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 147th largest of the 447 jobs that showed up at all; 6 of its 25 tasks showed up. Within each of Anthropic's methods, never across a change: 1.4% to 1.1% (released February and March 2025); 0.94% to 0.95% (August 2025 to February 2026); 0.12% to 0.12% (April to May 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | 1.4% | 12 of 708 | 19 of 25 |
| Released March 2025 | 1.1% | 13 of 703 | 18 of 25 |
| The week of Aug 4, 2025 (released September 2025) | 0.94% | 21 of 655 | 18 of 25 |
| The week of Nov 13, 2025 (released January 2026) | 1% | 20 of 672 | 18 of 25 |
| The week of Feb 5, 2026 (released March 2026) | 0.95% | 23 of 677 | 17 of 25 |
| April 2026 (released June 2026) | 0.12% | 141 of 434 | 6 of 25 |
| May 2026 (released June 2026) | 0.12% | 147 of 447 | 6 of 25 |
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
6% of the working time: the conversation, in-person and hands-on parts of the tasks.
- Gather requirements with architects, the conversation, 2%
- Coordinate development with the team, the conversation, 2%
- Set and enforce development standards, the conversation, 1%
- Demonstrate database capabilities, the conversation, 0.8%
- Support staff and clients, the conversation, 0.5%
What becomes checking the machine
85% 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.
- Develop database strategies, costly if wrong, 10%
- Design database applications, costly if wrong, 10%
- Document database architectures, costly if wrong, 9%
- Integrate database products, costly if wrong, 9%
- Design databases for applications, costly if wrong, 8%
- Model application data structures, costly if wrong, 8%
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 85% 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.
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 . 25 tasks from .
| Task | ||||
|---|---|---|---|---|
| Design database applications, such as interfaces, data transfer mechanisms, global temporary tables, data partitions, and function-based indexes to enable efficient access of the generic database structure.Design work on paper and in code.Done more than yearly by most who do it. AI observed on this task. | 10% | 2.1 work days3.3 h to 1.3 work weeks | Documents 100% | 18%Half by Jul 2027 |
| Develop database architectural strategies at the modeling, design and implementation stages to address business or industry requirements.Working out the architecture on paper at each stage.Done more than monthly by most who do it. AI observed on this task. | 10% | 3.3 work days6.7 h to 1.7 work weeks | Documents 100% | 10%Half by Sep 2027 |
| Develop and document database architectures.Designing the architecture and writing it up.Done more than weekly by most who do it. AI observed on this task. | 10% | 4.2 work days6.7 h to 2.5 work weeks | Documents 100% | 6%Half by Feb 2028 |
| Design databases to support business applications, ensuring system scalability, security, performance, and reliability.Design work on paper and in the modeling tool.Done more than monthly by most who do it. | 10% | 4.2 work days6.7 h to 3.3 work weeks | Documents 100% | 5%Half by Apr 2028 |
| Develop methods for integrating different products so they work properly together, such as customizing commercial databases to fit specific needs.Working out how the products fit together and configuring them to.Done more than weekly by most who do it. | 10% | 4.2 work days6.7 h to 2.5 work weeks | Documents 70%, systems 30% | 6%Half by Feb 2028 |
| Develop data models for applications, metadata tables, views or related database structures.Designing the tables, views and metadata on paper and in the modeling tool.Done more than weekly by most who do it. AI observed on this task. | 8% | 1.7 work days3.3 h to 1 work week | Documents 100% | 28%Half by Apr 2027 |
| Develop data model describing data elements and their use, following procedures and using pen, template or computer software.Drawing and documenting how the data items relate.Done more than weekly by most who do it. | 6% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%Half by now |
| Create and enforce database development standards.Writing the standards and holding the team's work to them.Done more than monthly by most who do it. AI observed on this task. | 5% | 1.7 work days3.3 h to 4.2 work days | Documents 80%, conversation 20% | 25%Desk part half by Mar 2027 |
| 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 monthly by most who do it. | 5% | 6.7 h2.5 h to 3.3 work days | Documents 80%, systems 20% | 59%Half by now |
| 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. | 4% | 6.7 h1.7 h to 2.5 work days | Documents 100% | 55%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 monthly by most who do it. | 3% | 5 h1.7 h to 2.1 work days | Documents 100% | 73%Half by now |
| Work as part of a project team to coordinate database development and determine project scope and limitations.Team meetings to settle scope and limits, and the write-ups.Done more than weekly by most who do it. | 3% | 2.5 h50 min to 1.3 work days | Conversation 60%, documents 40% | 35%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).
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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 Architects is within reach of AI now?
- An estimated 28% of the working time is within reach of AI models now and 89% by the end of 2028, on METR's long-run pace at four in five (66% to 94% 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 Architects 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 data models (55% of the task's time now, 100% by the end of 2028); Code database descriptions (59% of the task's time now, 100% by the end of 2028); and Model application data structures (28% of the task's time now, 99% by the end of 2028).
- Which tasks of Database Architects 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 0% of the working time, and the people and body parts of the other tasks stay with people too.
- What should Database Architects 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; and briefing a model and checking its drafts. By the end of 2028 on the long-run pace at four in five, about 6% of the working time stays with people, 85% 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 Architects?
- 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 147th largest share of the 447 jobs that showed up; 6 of its 25 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 58%. 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 Architects?
- 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 25 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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