As of August 2026, Database Architects has an AI-exposure score of 71/100 (High exposure) on the AI-Safe Careers index. This is an estimate of task exposure, not a prediction of job loss.
Score inputs for this role: This role starts from O*NET 29.1 occupational descriptors and is empirically grounded by Penn/OpenAI GPTs are GPTs study, Anthropic Economic Index (June 26, 2026). BLS labor-market figures are separate context, not score inputs.

AI Exposure Score for

Database Architects

71/100
High exposure
LowModerateElevatedHighVery High

More exposed than 91% of the roles we track. Median pay ~US$139,500. About 4,000 projected openings a year (BLS 2024–34 - growth plus replacement).

Pay & demand figures are US medians (BLS, in USD) - your local figures will differ. Your exposure score applies broadly.

Will AI replace Database Architects?

No exposure score can predict whether AI will replace this role. The 71/100 score means our current model estimates high task exposure from the sources listed on this page. It does not predict an employer decision, headcount, or an individual outcome. The task map below shows the work assessed and where human judgment remains important.

Early-career context (study ages 22-25)

This role is in the High exposure band, but its assessed task mix is not automation-heavy. The study found the decline concentrated where AI was more likely to automate rather than augment work, so the headline figure should not be applied directly.

The November 2025 revision reports a 16% relative employment decline for workers ages 22-25 in the most AI-exposed U.S. occupations, after firm-level controls, relative to workers in less-exposed fields and more experienced workers in the same occupations.

Use the task map to identify durable work and the skills worth building early.

Stanford Digital Economy Lab, Canaries in the Coal Mine - November 2025 revision

This is group-level U.S. payroll evidence, not a personal forecast. The authors do not claim that AI alone caused the change, and this context does not alter the exposure score.

Data sources, not endorsements: O*NET and curated role data; empirical AI signals where matched; BLS employment, pay, and demand as separate context.Methodology Data sources
Role snapshot

What this role usually involves

O*NET 29.1 exact occupation

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.

Common titles
Database AnalystDatabase DeveloperDatabase ProgrammerInformation ArchitectData ArchitectData Engineer
O*NET job-zone preparation
Job Zone 4 · Considerable Preparation Needed Most of these occupations require a four-year bachelor's degree, but some do not. A considerable amount of work-related skill, knowledge, or experience is needed for these occupations.

Broad guidance for this preparation level; exact requirements vary by role and employer.

Skills and knowledge
Complex Problem SolvingCritical ThinkingJudgment and Decision MakingReading ComprehensionSystems AnalysisSpeaking
Work context
Decision latitudeIndoor controlled settingFrequent contact with othersRepeating tasksConsequence of error

Source: O*NET 29.1 exact occupation - Database Architects, SOC 15-1243.00. Context describes the role; the AI-exposure score remains a separate task-exposure estimate.

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Database Architects tasks, by AI exposure

Automatable

No automatable tasks identified for this role - its individually-assessed tasks split 90% augmentable / 10% durable.

Augmentable
  • Demonstrate database technical functionality, such as performance, security and reliability.
  • Identify, evaluate and recommend hardware or software technologies to achieve desired database performance.
16 more augmentable tasks locked in the report.
Durable
  • Develop database architectural strategies at the modeling, design and implementation stages to address business or industry requirements.
  • Collaborate with system architects, software architects, design analysts, and others to understand business or industry requirements.

We analyzed all 20 Database Architects tasks - 18 augmentable and 2 durable. The full task map - every task with exactly what to do about each - is in your Career Report.

Your report unlocks three concrete artifacts

Full task map

Every task scored with what to automate, augment, or protect.

Adjacent path comparison

Related roles with exposure deltas, salary, demand, and reachability. Lower-exposure options appear only when the data supports them.

30/60/90 plan + PDF

A keepable roadmap plus resume and LinkedIn repositioning.

Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate - not generic advice.

Adjacent career paths

Relatedness shows how reachable a move may be. A path is labeled lower exposure only when its score is at least 6 points lower; every row shows the measured difference.

Database Administrator
40% skills overlap; 10 points lower - lower exposure; Elevated band; ~US$101,000
View path
61
7 more adjacent paths with exposure deltas, salary, demand, and reachability in your Career Report.
Agent Reality Check (on-site workflow preview)

Demonstrate database technical functionality, such as performance, security and reliability.

Check what deployed AI agents can attempt on tasks like this using dated capability evidence. You review the real task before any analysis runs.
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Your AI-Safe Career Report

Every task scored with what to do about it; adjacent paths with honest exposure deltas, salary, demand, and reachability; a skill-gap map; a 30/60/90-day roadmap; Agent Reality Check; plus a résumé and LinkedIn rewrite and professional PDF.
Grounded in O*NET-linked or curated role data, with Penn, Anthropic Economic Index, and AIOE signals where matched. BLS labor-market context is separate.

AI was the most-cited reason for U.S. layoffs through mid-2026 - the workers who adapt earliest fare best. - Challenger, Gray & Christmas, 2026The upside: Workers with AI skills earn a roughly 62% wage premium - adapting pays. - PwC Global AI Jobs Barometer, 2026

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Important: This is an estimate of AI exposure, not a prediction that your job will disappear. It is designed to help you understand how your role may change and improve your career resilience.

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Database Architects - median pay by US state (BLS OEWS, USD)

California: US$170,160Texas: US$151,370New York: US$141,350Florida: US$138,320

Median annual wage, in USD. US national: US$139,500. More states are being added.

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