Will AI replace Database Administrators?

Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Database Administrators (United States, SOC 15-1242), 82% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 67 out of 100 (range 61–73, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.

Which tasks in “Database Administrators” can AI already do?

The highest-scoring tasks in release 2026-q4.1 are: “Review procedures in database management system manuals to make changes to database” (83/100, very high); “Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions” (83/100, very high); “Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information” (75/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.

Which tasks in “Database Administrators” stay human?

About 6% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Train users and answer questions” (30/100, low); “Provide technical support to junior staff or clients” (40/100, partial); “Approve, schedule, plan, and supervise the installation and testing of new products and improvements to computer systems, such as the installation of new dat…” (43/100, partial). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.

What should someone working in “Database Administrators” do about AI?

Start from the ledger rather than the headline: 82% of this job's weighted core work is exposed, and roughly 6% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.

How is the AI exposure score for Database Administrators calculated?

Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 18 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

US dataswitch to UK

Database Administrators

modifying existing databases and database management systems or directing programmers and analysts to make changes, training users and answering questions and providing technical support to junior staff or clients. If that's your week, this page is about your job.

The honest answer

Most tasks in this job are the kind AI has learned to do: testing changes to database applications or systems. The tasks, though, are not you.

Your move: three real directions from here ↓

Where the work sits, by task weight

shifting to AI: 82%
changing shape: 12%
staying human: 6%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

Whole-job exposure score 67 out of 100 (61–73 allowing for uncertainty): high exposure, across 18 scored tasks. The number is the support for the sentence above it, not a headline about anyone’s future.

How we know this

What is measured: Every published task statement for database administrators is rated on five dimensions: can a model produce the output, does the work need a body in a room, does it need a legally accountable person, does it depend on a person being trusted in the moment, and how much data exists. A published formula turns those five ratings into the score; the model never writes the number.

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

It would be a lie to soften that, and another lie to promise a rebuilt version of this job inside this job.

So the hope here is what you already carry: the judgment you bring to users is real, and the moves below are built from it. The first step is down this page.

Your week, as this page understands it

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. The job title says “database administrators”. The real job is the part underneath: training users and answering questions. That is the thing someone has to be right about.

The exposed part of this job is specific, and we won’t pretend it is coming back. But database administrators is not one task. It is 18 scored ones, and they are nowhere near equally exposed. The most durable of them, on this evidence, is training users and answering questions, and the ledger below shows exactly why.

Where the work sits, by task weight

shifting to AI: 82%
changing shape: 12%
staying human: 6%

These bars are tasks changing hands, not people being counted out. The ledger below shows which.

How we know this

How the bar is built: Each task’s share of the bar is its published importance weight, so a task you do all day counts for more than one you do twice a year.

Release: 2026-q4.1, scores computed 2026-08-05. Read the full method.

Your job, task by task

These are the official task statements for this occupation, in plain English, sorted by what the evidence says is happening to each one. The official wording sits under every line so you can check the rewrite against it.

8 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Shifting to AI

15 tasks

Tasks today’s tools can already do most of. This is the part we will not soften: where these rows are the bulk of your week, the week changes.

Modifying existing databases and database management systems or directing programmers and analysts to make changes
This is reading one thing and writing another: databases in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Modify existing databases and database management systems or direct programmers and analysts to make changes.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Making changes to a database is well-understood work coding tools handle, with a person checking before it goes live.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Testing changes to database applications or systems
This is reading one thing and writing another: changes in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Test changes to database applications or systems.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Testing database changes is largely scripted already, with tools generating and running the checks.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Testing programs or databases, correct errors and making necessary modifications
This is reading one thing and writing another: programs in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Test programs or databases, correct errors, and make necessary modifications.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Finding and fixing errors in databases is work coding assistants now do to a reviewable standard.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Specifying users and user access levels for each segment of database
This is reading one thing and writing another: users in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Specify users and user access levels for each segment of database.” (O*NET task statement)
How this row was scored
Exposure score: 68 out of 100 (61–75 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; mistakes that are cheap to catch.
The rating behind it: The method is standard, but deciding which named people should see which data depends on local knowledge.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 2/4.
Planning, coordinating
This is reading one thing and writing another: security measures in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Plan, coordinate, and implement security measures to safeguard information in computer files against accidental or unauthorized damage, modification or disclosure.” (O*NET task statement)
How this row was scored
Exposure score: 64 out of 100 (57–71 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Standard database security controls are well documented, though rolling them out needs coordination with the people affected.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.
Planning and installing upgrades of database management system software to enhance database performance
This is reading one thing and writing another: upgrades of database management system software in, a record out. That is the shape today's tools are built for.
importance 4 · Core
Source: “Plan and install upgrades of database management system software to enhance database performance.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Upgrade planning follows vendor procedures software can lay out, with a person watching the actual run.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Writing and coding logical and physical database descriptions and specifying identifiers of database to management system
This is reading one thing and writing another: logical in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (79–87 allowing for uncertainty): very high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Writing database definitions is code, and code in documented languages is what these tools do best.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.

Changing shape

2 tasks

Tasks where the machine takes the producing and a person keeps the checking, the deciding, or the answering-for-it. For most jobs this is the biggest group, and it is where "transformation, not termination" is literally visible.

Providing technical support to junior staff or clients
The software now makes the first pass at technical support, but the part that matters is a person saying it and standing behind it. So the job becomes checking and deciding rather than producing.
importance 3 · Core
Source: “Provide technical support to junior staff or clients.” (O*NET task statement)
How this row was scored
Exposure score: 40 out of 100 (33–47 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Answers can be drafted, but supporting junior staff and clients depends on someone they can come back to.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.
Approving, scheduling, planning and supervising the installation and testing of new products and improvements to computer systems
The software now makes the first pass at the installation, but the deciding part still needs a person. So the job becomes checking and deciding rather than producing.
importance 3 · Core
Source: “Approve, schedule, plan, and supervise the installation and testing of new products and improvements to computer systems, such as the installation of new databases.” (O*NET task statement)
How this row was scored
Exposure score: 43 out of 100 (36–50 allowing for uncertainty): partial exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Software can plan and schedule an installation, but approving and supervising it is a responsibility a person carries.
The five ratings: output a model can produce 2/4 · needs a body in a room 0/4 · needs an accountable person 1/4 · needs to be trusted in the moment 1/4 · how much data exists 3/4.

Staying human

1 task

Tasks that stay with a person, because they happen in the physical world, because the rules need someone accountable, or because the value is that a specific person does them.

Training users and answering questions
The value here is that a specific person handles users and stands behind it. That is earned, not computed.
importance 4 · Core
Source: “Train users and answer questions.” (O*NET task statement)
How this row was scored
Exposure score: 30 out of 100 (23–37 allowing for uncertainty): low exposure, medium confidence.
Why it sits in this group: the same decision, made over and over; the value is that a specific person does it.
The rating behind it: Training material writes itself easily; training people and answering their follow-ups still works better with a person.
The five ratings: output a model can produce 2/4 · needs a body in a room 1/4 · needs an accountable person 0/4 · needs to be trusted in the moment 2/4 · how much data exists 3/4.

Show the other 8 tasks

Reviewing procedures in database management system manuals to make changes to database
shifting to AI
This is reading one thing and writing another: procedures in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Review procedures in database management system manuals to make changes to database.” (O*NET task statement)
How this row was scored
Exposure score: 83 out of 100 (76–90 allowing for uncertainty): very high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading vendor manuals and applying the right procedure is exactly what software does well with public documentation.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 4/4.
Developing standards and guidelines for the use and acquisition of software and to protect vulnerable information
shifting to AI
This is reading one thing and writing another: standards in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Drafting software and data-protection standards is written policy work software produces well before a person adapts it.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Developing data models describing data elements and how they
shifting to AI
This is reading one thing and writing another: data models describing data elements in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Develop data models describing data elements and how they are used, following procedures and using pen, template, or computer software.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (71–79 allowing for uncertainty): high exposure, high confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Producing data models from described requirements is drafting work software does well before review.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Selecting and entering codes to monitor database performance and to create production databases
shifting to AI
This is reading one thing and writing another: codes in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Select and enter codes to monitor database performance and to create production databases.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Setting up performance monitoring and creating databases follows documented patterns software can generate.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Reviewing workflow charts developed by programmer analyst to understand tasks computer will perform
shifting to AI
This is reading one thing and writing another: workflow charts in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Review workflow charts developed by programmer analyst to understand tasks computer will perform, such as updating records.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Reading and making sense of workflow charts is the kind of document work current tools handle well.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Revising company definition of data as defined in data dictionary
shifting to AI
This is reading one thing and writing another: company definition of data in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Revise company definition of data as defined in data dictionary.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Updating data dictionary definitions is documentation work software drafts from the existing records.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Identifying, evaluating and recommending hardware or software technologies to achieve desired database performance
shifting to AI
This is reading one thing and writing another: hardware in, a record out. That is the shape today's tools are built for.
importance 3 · Core
Source: “Identify, evaluate and recommend hardware or software technologies to achieve desired database performance.” (O*NET task statement)
How this row was scored
Exposure score: 75 out of 100 (68–82 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Recommending technology needs knowledge of the existing estate and budgets, though tools produce a strong comparison to start from.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 0/4 · how much data exists 3/4.
Identifying and evaluating industry trends in database systems to serve as a source of information and advice for upper management
shifting to AI
This is reading one thing and writing another: industry trends in, a record out. That is the shape today's tools are built for.
importance 3 · Supplemental
Source: “Identify and evaluate industry trends in database systems to serve as a source of information and advice for upper management.” (O*NET task statement)
How this row was scored
Exposure score: 70 out of 100 (63–77 allowing for uncertainty): high exposure, medium confidence.
Why it sits in this group: reading one thing and writing another; the same decision, made over and over; mistakes that are cheap to catch.
The rating behind it: Tracking industry trends and writing them up for management is research and summary work software does quickly.
The five ratings: output a model can produce 3/4 · needs a body in a room 0/4 · needs an accountable person 0/4 · needs to be trusted in the moment 1/4 · how much data exists 4/4.

What this job pays, and how many people do it

Median pay: $104,620a year, the middle of the range, so half earn more and half earn less.bls-oews, 2025 · May 2025 estimates (national_M2025_dl.xlsx)
How we know this
Source: bls-oews
Reference period: May 2025 estimates (national_M2025_dl.xlsx)
Rounding: Shown as published.
People doing this job: 69,990in the US, 2025.bls-oews · May 2025 estimates (national_M2025_dl.xlsx)

What is deliberately not here: a forecast of how many of these jobs exist in ten years. Where an official projection exists for a market we publish it with its vintage; where it does not, we leave the space empty rather than borrow the other country’s number.

Why this is shifting

The reason is boringly specific. Most of what is shifting here is reading one thing and writing another: technical support in, a record out. The rows above are exactly that shape: testing changes to database applications or systems and modifying existing databases and database management systems or directing programmers and analysts to make changes. What it cannot do is be trusted in person, which is what users run on: someone specific doing it and standing behind it. Which is why this page talks about your tasks changing, not your job ending.

Your move

Over a pint: what I’d tell you if you were my friend

The exposed part of your job is the biggest part, and I am not going to dress that up: testing changes to database applications or systems is work today's tools do quickly and cheaply, and that is not coming back.

So, given all that: 82% of this job's task weight sits in rows the software is already learning, 12% in rows that change shape rather than disappear, and 6% in rows it is nowhere near. That is the position, measured across 18 scored tasks. It is not a forecast about you.

What you have that the software does not is training users and answering questions, plus the years of knowing when something looks wrong before you can say why. That is the raw material for everything below.

This week: one thing

Sit on the machine's side of the desk. Pick one real piece of technical support you would normally do yourself, let whatever software you already have take the first pass at it, and then go through what it produced and write down every single thing it got wrong. One evening this week. Do not fix anything yet. Just catch it.

What you end up holding: a written list of the machine’s mistakes, in your handwriting
How long it takes: an evening, or an hour if you pick one job rather than one client

If you can’t run software on your employer’s or your clients’ data: Do the same hunt on paper. Take one printed piece of technical support, work through it the way you always do, and mark every point where you made a call rather than followed a rule. Same evening, same list, nothing to log into and nobody to ask permission from. That list is the same artifact: it is the judgment written down.

Over the next 90 days

Change one sentence about what you do. Not on a CV. Out loud, to whoever pays you. From “my job is testing changes to database applications or systems” to “I check what the software does and tell you what it means.” Your error list from this week is what makes that sentence true instead of a claim, so use it: show it once, to one person, inside the next ninety days. Same skills, priced as judgment rather than as typing.

Over the next 12 months

Walk toward the end of this job that answers for things, and get it recognised. Pick the one part of training users and answering questions you are already best at, and spend the year making it formal: a qualification, a named responsibility, a specialism people ask for by name. Price it honestly: that is evenings, it is months rather than weeks, and the seats are competitive because everyone in your position is looking at the same door. Before you pay for anything, use CareerOneStop - Find local training. It is free, it is the Labor Department's own service, and it is listed below with the rest of the free routes.

The roads out of here, and why I am not sending you down them

I looked at the obvious moves out of this job, and here is what I found.

I checked the 12 nearest US occupations to database administrators (nearest by the work that AI is not taking, not by job title), and none of them survived. The closest was database architects: only about 7% of its durable work is work you already do and it is under the same pressure this job is. I am not going to pretend that is comfortable news: 82% of your own task list is already in the top exposure band. But the answer on this evidence is not a sideways jump into a job with the same problem. It is to walk toward the end of this one that answers for things. “provide technical support to junior staff or clients” is the part that stays with a person, and spending a year getting formally recognised for it beats a standing start somewhere else.

How that was checked: this job was compared against all 830 US occupations in this release on their official task statements, and the 12 nearest were examined one by one. A move that turns on an industry, an employer or a qualification rather than on the work itself will not show up in a check like that. And this release carries no licence register, so anything you are weighing needs that looked up separately.

3 moves I checked and rejected

These are the obvious-looking jumps. They are here with their reasons rather than quietly dropped, because the ones that fail are worth knowing about. It is one less thing to turn over at night.

Database Architects
Why it looked obvious: It came up as a near neighbour because one of your tasks is on their list in the same words: “provide technical support to junior staff or clients”. Across the whole of both lists that adds up to about 7% of the work in that job the software is not taking.
Why I am not recommending it: Almost none of it is work you already do: about 7% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 83% of its own task list already scores in the top exposure band (71/100 in this release), so the same software is eating it.
Look at that job’s page anyway →
Mathematical Science Occupations, All Other
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already review procedures in database management system manuals to make changes to database, and their equivalent is to confer with database users about project timelines and changes. Across both published task lists that is about 6% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 6% of the durable side of that job. That is a different job, not a next step. I will not move you off one melting floe onto another: 85% of its own task list already scores in the top exposure band (78/100 in this release), so the same software is eating it. It is a pay cut, in those words: $81,490 against your $104,620, 22.1% less (OEWS May 2025 (both)). Retraining to earn less is a decision, not advice. And it is a narrow door: about 3,720 of those jobs against 69,990 of yours (OEWS May 2025), 5% as many seats.
Look at that job’s page anyway →
Computer and Information Systems Managers
Why it looked obvious: It came up as a near neighbour on the work AI is not taking: you already provide technical support to junior staff or clients, and their equivalent is to provide users with technical support for computer problems. Across both published task lists that is about 5% of the durable work in that job.
Why I am not recommending it: Almost none of it is work you already do: about 5% of the durable side of that job. That is a different job, not a next step.
Look at that job’s page anyway →

What I’d stop worrying about

A friend tells you what not to spend fear on. This is that list.

The headline number you read somewhere
The big “X% of jobs” figures are about the whole economy, not about you. The number that describes your job is on this page: 82% of its task weight, across 18 scored tasks. Every row behind it is printed above with the source. Check ours; ignore theirs.
“It’s too late for me to become something else”
You are not starting from zero, and the page shows why: training users and answering questions is work the software cannot do and you already do it. The move above is a repricing of what you know, not a new career. Nobody who has just left college has that.
“I should learn to code”
Almost certainly not. The value in your job is moving toward checking, deciding and answering for the output, not toward writing the software. A weekend of Python will not change your position; the error list from this week will.
The “obvious” next job everyone suggests
I checked the obvious moves and most of them did not survive. The reasons are printed with the routes above, including the pay and the gate. A move that fails on the numbers is worth knowing about so you can stop turning it over at night.

You are reading the United States figures

The United Kingdom splits this work across more than one official group, of which Database administrators and web content technicians is the closest. The pay and employment figures are not directly comparable, and we do not average them together.

Switch to the United Kingdom page →partial match

In UK official statistics this job is counted as Database administrators and web content technicians. Pay and employment stay on this page’s own group; the task list and the scores do not cross over.

Your route through this

Where to go next, and what it costs

Free, and complete

The moves above cost nothing. These are the real services that go with them: public, government-funded, and free at the point of use. Nothing on this page is behind an email address or a payment.

Anywhere in the US:
CareerOneStop - Find local training
Search what's running near you, from the Labor Department's own database, before anyone sells you a course.
Free to search; individual programs vary, and some are funded
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No Space for this job, but one for what is happening to it

Nothing Collab365 runs is built for database administrators, and we are not going to point you at the nearest one and call it a fit.

There is one that is not about a job title at all. The AI Authority is about being the person who directs these tools at work rather than the person they get compared to. That is worth saying here, because 82% of the work on this page is already inside what they can do.

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7 days free, no card needed. Explore up to 2 Spaces before you choose a plan: you pick a plan later, not now.

The AI Authority is a general community about working with AI, not a course for database administrators. You do not need it to act on anything here: the moves above cost nothing and stand on their own. The data on this page is the same either way.

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No Space for database administrators yet. Should there be one?

Collab365 Spaces is built by the same people as this site. We find the problems that AI and automation are creating inside one kind of work, then solve them as short courses, briefings and Blueprints. Each Space is the community too, so the research and the people doing your job are in the same place.

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Collab365 launches new communities where the need is real. If one for database administrators existed, with researched problems, courses and people in the same boat, would you want in?

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This unlocks nothing. Every figure, every row and every step on this page is already yours, whether you fill this in or not.

No deadline on any of this. The page will still be here, and the data is refreshed on a published schedule rather than when someone wants a headline.

Questions people ask about this job

Will AI replace Database Administrators?: Not as a job, but it is already doing parts of the work. Across the 18 official task statements scored for Database Administrators (United States, SOC 15-1242), 82% of the importance-weighted core work is made of tasks today's AI could already do most of. The overall exposure score is 67 out of 100 (range 61–73, band: high). That is a statement about tasks, not about headcount: this measures what AI could do, not whether any employer adopts it, whether the law allows it, or whether doing the routine parts faster creates more demand for the human parts. Figures are from release 2026-q4.1.
Which tasks in “Database Administrators” can AI already do?: The highest-scoring tasks in release 2026-q4.1 are: “Review procedures in database management system manuals to make changes to database” (83/100, very high); “Write and code logical and physical database descriptions and specify identifiers of database to management system, or direct others in coding descriptions” (83/100, very high); “Develop standards and guidelines for the use and acquisition of software and to protect vulnerable information” (75/100, high). Each score comes from five published 0–4 ratings turned into a number by a published formula, and each carries the model's one-sentence reason on the page.
Which tasks in “Database Administrators” stay human?: About 6% of this job's task weight sits in work that scores low for AI exposure. The lowest-scoring tasks in release 2026-q4.1 are: “Train users and answer questions” (30/100, low); “Provide technical support to junior staff or clients” (40/100, partial); “Approve, schedule, plan, and supervise the installation and testing of new products and improvements to computer systems, such as the installation of new dat…” (43/100, partial). Low scores usually mean the task needs a body in a room, a legally accountable human, or trust built in real time. Those are the three things the scoring rubric treats as gates rather than obstacles.
What should someone working in “Database Administrators” do about AI?: Start from the ledger rather than the headline: 82% of this job's weighted core work is exposed, and roughly 6% is not. The practical move is to spend more of your week on the tasks that score low, the ones above, and to get fluent at directing AI through the tasks that score high, because those are the parts that change whether or not you are ready for them. This page does not predict your job, and nothing here is career advice tailored to you: the score describes the occupation, not the person.
How is the AI exposure score for Database Administrators calculated?: Each official task statement for the occupation is rated on five published 0–4 dimensions (output replicability, physical embodiment, licensed accountability, real-time human trust, and data availability) by claude-opus-5 using scoring prompt task_scoring_v1.0. The model never writes the score; a published formula turns the five ratings into a 0–100 number, so every score can be recomputed by hand. The occupation figure is the importance-weighted mean across 18 scored tasks. The prompt, the rubric, the formula and the full dataset are published at https://futureproof.collab365.com/method and https://futureproof.collab365.com/data/2026-q4.1 under CC BY 4.0.

Where these numbers come from

Worth knowing about these figures

The match between this job and its counterpart in the other country is partial, so the two pages count slightly different groups of people.
8 of this occupation's scored task statements carry a score that was measured under a different occupation's context, because the statement is shared between jobs and has only been scored once so far. Each one names the occupation it was measured under in the free routes below; none is presented as a measurement for this job.
Task clusters are not derived in this release, so the task-cluster field is empty and no Collab365 Space routing is attached to this occupation yet.

Task statements: onet-dbProcessing: catalogue-bridge → onet-im-rt-weighting → task-scoring → score-aggregation
Task weights: onet-db (im-rt)
Scores: Rubric task_scoring_v1.0, model claude-opus-5, computed 2026-08-05.
Pay and employment: bls-oews (May 2025 estimates (national_M2025_dl.xlsx))bls-oews (May 2025 estimates (national_M2025_dl.xlsx))

Figures on this page come from release 2026-q4.1, published 2026-08-05. Every release keeps its own permanent address, so a figure you cite in March is still there, unchanged, in November.

The plain-English wording on this page is assembled directly from the task statements and the published ratings, not written by hand for this occupation. That is why it is specific, and it is also why we say so.

The routes and free resources further up are today’s, not the release’s (last reviewed 2026-08-05). A route is an offer, not a historical fact, so it moves on its own clock.

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Everything on this site is published under CC BY 4.0. Quote it, chart it, sell something built on it. Just say where it came from, and cite the dated release rather than the site, so the figure you quote stays checkable.

Plain text

Collab365 (2026). Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1 (methodVersion 2.0.0, promptVersion task_scoring_v1.0). https://futureproof.collab365.com/data/2026-q4.1. Licensed CC BY 4.0. Built with O*NET data (USDOL/ETA, CC BY 4.0); ONS data (Open Government Licence v3.0); GAISI task framework (arXiv:2507.22748, MIT); BLS data (public domain).

BibTeX

@misc{collab365futureproof2026q41,
  title        = {Collab365 Futureproof: task-level AI exposure for US and UK occupations, release 2026-q4.1},
  author       = {{Collab365}},
  year         = {2026},
  url          = {https://futureproof.collab365.com/data/2026-q4.1},
  note         = {Release 2026-q4.1, methodVersion 2.0.0, promptVersion task_scoring_v1.0, CC BY 4.0}
}

Permalink

https://futureproof.collab365.com/data/2026-q4.1

Data as of release 2026-q4.1, published 2026-08-05. Releases never change after publication; when the figures move, a new dated release is published beside this one and this one stays exactly where it is.