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Computer and MathematicalData Warehousing Specialists15-1243.01 · 2026-Q4
66% AI does it34% AI helps0% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 0%AI helps 34%AI does it 66%
Each ridge is a slice of the job's task time.Needs a human 0%AI helps 34%AI does it 66%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Data Warehousing Specialists, O*NET-SOC 15-1243.01. 0% of the job’s task time still needs a human, so 0 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from O*NET, and where AI stands on each today. 0% of the task time still needs a human.

Each block is one task; its height is its share of working time.Needs a human 0%AI helps 34%AI does it 66%
The job's task list: the parts AI can do are blacked out.Needs a human 0%AI helps 34%AI does it 66%
Develop data warehouse process models, including sourcing, loading, transformation, and extraction.AI does it
Verify the structure, accuracy, or quality of warehouse data.AI helps
Map data between source systems, data warehouses, and data marts.AI helps
Develop and implement data extraction procedures from other systems, such as administration, billing, or claims.AI does it
Design and implement warehouse database structures.AI helps
Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.AI does it
Provide or coordinate troubleshooting support for data warehouses.AI does it
Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.AI does it
Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements.AI does it
Perform system analysis, data analysis or programming, using a variety of computer languages and procedures.AI does it
Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.AI does it
Create or implement metadata processes and frameworks.AI does it
Review designs, codes, test plans, or documentation to ensure quality.AI helps
Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing.AI helps
Select methods, techniques, or criteria for data warehousing evaluative procedures.AI does it
Implement business rules via stored procedures, middleware, or other technologies.AI does it
Prepare functional or technical documentation for data warehouses.AI does it
Test software systems or applications for software enhancements or new products.AI helps

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is graded A to D, and vendor studies are labelled as such.

When could it be replaced?

Could be largely automated 2033–2040

80% of scenarios between 2033 and 2040. A range from our scenario model of capability, adoption and friction, not a forecast that the job ends.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten scenarios behind its replacement range.

Today
Will AI replace this job?
Partly.
By 2045
100%
of our scenarios have AI largely doing this job by 2045 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)
By 2060
100%
of our scenarios have AI largely doing this job by 2060 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could partly do this job (Partly.)100%Today2030: 40.0% of scenarios: AI could partly do this job (Partly.)40%2030: 60.0% of scenarios: AI could mostly do this job (Mostly.)60%20302035: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2035: 70.0% of scenarios: AI could largely do this job (Largely.)70%20352040: 100.0% of scenarios: AI could largely do this job (Largely.)100%20402045: 100.0% of scenarios: AI could largely do this job (Largely.)100%20452050: 100.0% of scenarios: AI could largely do this job (Largely.)100%20502055: 100.0% of scenarios: AI could largely do this job (Largely.)100%20552060: 100.0% of scenarios: AI could largely do this job (Largely.)100%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%100.0%0.0%0.0%
20300.0%60.0%40.0%0.0%0.0%
203570.0%30.0%0.0%0.0%0.0%
2040100.0%0.0%0.0%0.0%0.0%
2045100.0%0.0%0.0%0.0%0.0%
2050100.0%0.0%0.0%0.0%0.0%
2055100.0%0.0%0.0%0.0%0.0%
2060100.0%0.0%0.0%0.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from O*NET work context, licensing and the evidence we have.

Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
LiabilityMistakes are rated 2.2 out of 5 for consequence and decisions 3.3 out of 5 for impact; someone has to answer for them.
Clients want a personFace-to-face contact is rated 4.5 and physical closeness 2.8 out of 5; caring for or serving people is 1.8 out of 5 in importance.
LicensingUsual entry requirement (BLS): bachelor's degree.
RegulationWorkers rate responsibility for others' health and safety 1.5 out of 5.
Physical work0% of the task time is physical.

What would it cost to hand the work to AI?

The share of the year AI could handle (1,265 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$130–$12,650
A person’s wage for the same hours
$52,430–$124,030

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

0%
of the task time is physical work
None needed
the kind of robot the physical work would need
Little of this job is physical, so robotics is not what holds AI back.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 0%AI helps 34%AI does it 66%
Writing · 12.9% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 25% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 62.1% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 0% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 0% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 0% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 0% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 0% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 0%AI helps 34%AI does it 66%
How exposed is it?

Still needs a human: 52/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 0% needs a human, 34% AI helps, 66% AI does it. Still needs a human: 52/100 ↑ safer. Will AI replace them? Partly.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 52/100 ↑ safer. Will AI replace them? Partly.

ChatGPTPartly

AI will automate many routine data warehousing tasks, but specialists will still be needed for architecture, governance, business context, and complex decision-making.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudePartly

AI will automate many routine data warehousing tasks (pipeline optimization, schema design, query tuning), but human specialists will still be needed for strategic architecture decisions, business context understanding, and overseeing complex system integrations.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI will automate routine tasks like ETL pipeline generation, data modeling, and query optimization, human specialists will still be essential for strategic architecture, complex business alignment, and data governance.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate routine warehousing tasks, but specialists who handle architecture, governance, integration, and business-critical judgment are unlikely to be fully replaced within the next decade.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Data Warehousing Specialists? Partly. Still needs a human: 52/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/data-warehousing-specialists/ (accessed 3 October 2026).

Scores change with each release, so cite the release. The data is open under CC BY 4.0: credit NeedsAHuman.com with a link. Open data · Press

Put the badge on your site

The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: O*NET 31.0, US Department of Labor (CC BY 4.0).
  • Jobs, pay and projections: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics and Employment Projections 2025–35.
  • How AI is used today: Anthropic Economic Index; Microsoft Research, "Working with AI".
  • What AI can do: our task ratings (rubric r1) and the quality evidence register.
  • UK names and employment: ONS SOC 2020 coding index and Annual Population Survey.

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.