# Clinical Research Coordinators

> Plan, direct, or coordinate clinical research projects. Direct the activities of workers engaged in clinical research projects to ensure compliance with protocols and overall clinical objectives. May evaluate and analyze clinical data.

- **SOC code:** 11-9121.01
- **Canonical URL:** https://singulariki.com/roles/role-11-9121-01
- **Also known as:** Clinical Program Manager, Clinical Research Coordinator, Clinical Trial Manager, Research Coordinator, Clinical Coordinator, Clinical Program Coordinator, Clinical Research Administrator, Clinical Research Manager
- **Frame:** "AI exposure" means task overlap (how codifiable the work is), not jobs lost or a forecast. Every figure below is traced to a named public dataset.

## What this work is

**Core tasks** (O*NET):
- Schedule subjects for appointments, procedures, or inpatient stays as required by study protocols.
- Perform specific protocol procedures such as interviewing subjects, taking vital signs, and performing electrocardiograms.
- Prepare study-related documentation, such as protocol worksheets, procedural manuals, adverse event reports, institutional review board documents, or progress reports.
- Assess eligibility of potential subjects through methods such as screening interviews, reviews of medical records, or discussions with physicians and nurses.
- Inform patients or caregivers about study aspects and outcomes to be expected.
- Record adverse event and side effect data and confer with investigators regarding the reporting of events to oversight agencies.
- Monitor study activities to ensure compliance with protocols and with all relevant local, federal, and state regulatory and institutional polices.
- Oversee subject enrollment to ensure that informed consent is properly obtained and documented.
- Maintain required records of study activity including case report forms, drug dispensation records, or regulatory forms.
- Dispense medical devices or drugs, and calculate dosages and provide instructions as necessary.
- Identify protocol problems, inform investigators of problems, or assist in problem resolution efforts, such as protocol revisions.
- Review proposed study protocols to evaluate factors such as sample collection processes, data management plans, or potential subject risks.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Customer and Personal Service _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Active Listening _(essential_skill)_
- Writing _(essential_skill)_
- Oral Comprehension _(ability)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Written Expression _(ability)_
- Problem Sensitivity _(ability)_
- Deductive Reasoning _(ability)_
- Speaking _(essential_skill)_
- Coordination _(transferable_skill)_

**Skills in demand:**
- Writing _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Active Listening _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Inductive Reasoning _(Common Skill)_
- English Language _(Common Skill)_
- Speech Recognition _(Specialized Skill)_
- Critical Thinking _(Common Skill)_
- Social Perceptiveness _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Time Management _(Common Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- IBM SPSS Statistics _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Word _(hot technology)_
- Python _(hot technology)_
- R _(hot technology)_
- SAS _(hot technology)_
- The MathWorks MATLAB _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 67th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 89th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 78th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 34th percentile (Moderate) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 13th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 3.7% growth (About average); 8.5k annual openings; 104.3k → 108.2k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $161,180; 100,870 employed.

## How people actually use AI here

Anthropic Economic Index — measured AI conversations mapped to this occupation's tasks:

- **Automation vs augmentation:** 64% automation, 27% augmentation (usage-weighted).
- **Autonomy median:** 3.5 (higher = AI acts more independently).
- **Dominant collaboration mode:** directive.

**Tasks most handed to AI here:**
- Code, evaluate, or interpret collected study data. _(7.3% of measured AI use; directive)_
- Prepare study-related documentation such as protocol worksheets, procedural manuals, adverse event reports, institutional review board documents, and progress reports. _(1.8% of measured AI use; task iteration)_
- Inform patients or caregivers about study aspects and outcomes to be expected. _(0.7% of measured AI use; learning)_
- Review proposed study protocols to evaluate factors such as sample collection processes, data management plans, and potential subject risks. _(0.6% of measured AI use; learning)_
- Participate in the development of study protocols including guidelines for administration or data collection procedures. _(0.5% of measured AI use; task iteration)_
- Collaborate with investigators to prepare presentations or reports of clinical study procedures, results, and conclusions. _(0.4% of measured AI use; directive)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me code, evaluate, or interpret collected study data.
- Help me prepare study-related documentation such as protocol worksheets, procedural manuals, adverse event reports, institutional review board documents, and progress reports.
- Help me inform patients or caregivers about study aspects and outcomes to be expected.
- Help me review proposed study protocols to evaluate factors such as sample collection processes, data management plans, and potential subject risks.
- Help me participate in the development of study protocols including guidelines for administration or data collection procedures.

## Sources

- **O*NET** (30.3) — U.S. Department of Labor / National Center for O*NET Development. https://www.onetcenter.org/database.html
- **BLS Occupational Employment and Wage Statistics (OEWS)** (May 2024) — U.S. Bureau of Labor Statistics. https://www.bls.gov/oes/
- **BLS Employment Projections** (2024–2034) — U.S. Bureau of Labor Statistics. https://www.bls.gov/emp/
- **Anthropic Economic Index** (v4 (2026-01-15) + v2 (2025-03-27)) — Anthropic. https://www.anthropic.com/economic-index
- **Microsoft “Working with AI”** (working-with-ai) — Microsoft Research. https://www.microsoft.com/en-us/research/
- **“GPTs are GPTs” (Eloundou et al.)** (arXiv 2303.10130) — OpenAI / academic. https://arxiv.org/abs/2303.10130
- **AI Occupational Exposure (AIOE)** (Felten, Raj & Seamans) — academic. https://github.com/AIOE-Data/AIOE
- **Frey & Osborne (2013)** (frey-osborne-automation) — academic. https://www.oxfordmartin.ox.ac.uk/publications/the-future-of-employment/
- **Dingel & Neiman (2020)** (dingel-neiman-workathome) — academic. https://github.com/jdingel/DingelNeiman-workathome

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_Generated from Singulariki's joined dataset; data snapshot 2026-06-02T21:00:32.945303+00:00. https://singulariki.com/roles/role-11-9121-01_