Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.
Work task
“Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.” is a core task performed by Materials Scientists. Among the occupation's 16 rated tasks, workers place it 12th by importance (#5 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.
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.
- 0.12% share of AI-use records mapped to this task
- 49% of that use is work-related
- Most common interaction: directive
- Average autonomy of the AI: 3.2 (1–5; higher = more autonomous)
- 95% 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
| Interaction pattern | Share | % | What it means |
|---|---|---|---|
| directive | 49% | you give the instruction; AI produces a finished result | |
| task iteration | 33% | you and AI go back and forth on the work | |
| learning | 12% | you ask AI to explain or teach you | |
| validation | 2% | you do the work; AI checks it |
Other tasks in this occupation
- Conduct research on the structures and properties of materials, such as metals, alloys, polymers, and ceramics, to obtain information that could be used to develop new products or enhance existing ones. · importance 4.4
- Test metals to determine conformance to specifications of mechanical strength, strength-weight ratio, ductility, magnetic and electrical properties, and resistance to abrasion, corrosion, heat, and cold. · importance 4.3
- Test material samples for tolerance under tension, compression, and shear to determine the cause of metal failures. · importance 4.2
- Determine ways to strengthen or combine materials or develop new materials with new or specific properties for use in a variety of products and applications. · importance 4.2
- Plan laboratory experiments to confirm feasibility of processes and techniques used in the production of materials with special characteristics. · importance 4.1
- Supervise and monitor production processes to ensure efficient use of equipment, timely changes to specifications, and project completion within time frame and budget. · importance 4.0
- Recommend materials for reliable performance in various environments. · importance 4.0
- Perform experiments and computer modeling to study the nature, structure, and physical and chemical properties of metals and their alloys, and their responses to applied forces. · importance 3.8
- Research methods of processing, forming, and firing materials to develop such products as ceramic dental fillings, unbreakable dinner plates, and telescope lenses. · importance 3.8
- Devise testing methods to evaluate the effects of various conditions on particular materials. · importance 3.8
- Test individual parts and products to ensure that manufacturer and governmental quality and safety standards are met. · importance 3.8
- Confer with customers to determine how to tailor materials to their needs. · importance 3.7
- Teach in colleges and universities. · importance 3.6
- Visit suppliers of materials or users of products to gather specific information. · importance 3.5
See all tasks on the Materials Scientists 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.
Cite this page
Singulariki. "Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.." Singulariki: a source-backed encyclopedia of work. Built from 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. https://singulariki.com/tasks/task-20214
Singulariki. (2026). Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.. Singulariki: a source-backed encyclopedia of work. Retrieved June 7, 2026, from https://singulariki.com/tasks/task-20214
@misc{singulariki-task-20214,
title = {Prepare reports, manuscripts, proposals, and technical manuals for use by other scientists and requestors, such as sponsors and customers.},
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-20214}
} Citations name the underlying public dataset releases — they reflect what this page is built from, not just the URL.