Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.

“Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.” is a core task performed by Data Warehousing Specialists. Among the occupation's 18 rated tasks, workers place it 11th by importance (#8 most important). About 100% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Design computer or information systems or applications. in Thinking Creatively
• Program computer systems or production equipment. in Working with Computers

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E1. Direct exposure — a language model could plausibly cut the time to do this task by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 1.00. Automation potential label: T3.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.31% share of AI-use records mapped to this task
• 57% of that use is work-related
• Most common interaction: directive
• Average autonomy of the AI: 3.7 (1–5; higher = more autonomous)
• 67% of interactions still needed a human in the loop

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Working with AI vs. handing it off

Of the AI conversations mapped to this task, the split between people working alongside AI and people delegating the task to it.

How people interact with AI on this task

Other tasks in this occupation

• Verify the structure, accuracy, or quality of warehouse data. · importance 4.4
• Develop data warehouse process models, including sourcing, loading, transformation, and extraction. · importance 4.4
• Map data between source systems, data warehouses, and data marts. · importance 4.2
• Develop and implement data extraction procedures from other systems, such as administration, billing, or claims. · importance 4.1
• Design and implement warehouse database structures. · importance 4.1
• 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. · importance 4.0
• Provide or coordinate troubleshooting support for data warehouses. · importance 3.9
• 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. · importance 3.9
• Perform system analysis, data analysis or programming, using a variety of computer languages and procedures. · importance 3.8
• Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow. · importance 3.8
• Create or implement metadata processes and frameworks. · importance 3.7
• Review designs, codes, test plans, or documentation to ensure quality. · importance 3.6
• Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing. · importance 3.6
• Select methods, techniques, or criteria for data warehousing evaluative procedures. · importance 3.6

See all tasks on the Data Warehousing Specialists page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-16120,
  title  = {Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-16120}
}