Database Designers and Administrators

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 6 task statements that define Database Designers and Administrators (ISCO-08 2521) score an average of 0.57 on a 0–1 exposure scale — more exposed than about 95% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 3 band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 6 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Designing, constructing, modifying, integrating, implementing and testing database management systems;”

Scores 0.67 on the 2025 scale. The task of designing, constructing, modifying, integrating, implementing, and testing database management systems is complex and involves a mix of routine and advanced technical skills. Generative AI can significantly assist with data organization, testing, and some aspects of modification and implementation, similar to tasks like "Creating and managing content management systems" which received an automation score of 0.7. AI technologies are proficient in automating routine components such as code generation and testing scripts but still require human expertise for complex decision-making, especially in design and strategic integration. Semantically similar tasks showed a range of automation potential based on the complexity and requirement of human oversight, with examples like operating and managing documentation ranging around 0.6 to 0.7. Considering the high technical capabilities required and the assistance GenAI can provide, especially in a technologically mature environment like Poland, an adjusted score of 0.68 is appropriate, reflecting substantial automation potential balanced with the need for human oversight and creative input.

Moving fastest, 2023 → 2025

“Designing and developing database architecture, data structures, tables, dictionaries and naming conventions for information systems projects;”

Model capability on this task changed by +0.33 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 2521, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

No U.S. role resolves through the crosswalk for this occupation. Search the encyclopedia for the closest match →

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Database Designers and Administrators sit at the 95th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Database Designers and Administrators rank in the 95th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure rose by 0.19 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Designing, constructing, modifying, integrating, implementing and testing database management systems;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Database Designers and Administrators". https://singulariki.com/gradient/2521-database-designers-and-administrators.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.