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AI Automation Index
Will AI Replace Clinical Data Managers?
Task-level automation exposure for Clinical Data Managers: 21 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
70%
weighted task index
21 of 21 tasks scored
Median Salary
$120,230 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
262,440 people hold this job — size, not growth
Projected 2025–35
+34.6%
employment change
24,800 openings a year · BLS line item
Pay by state
BLS OEWS publishes 50 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$69,490 – $163,350
Highest medians
Washington $163,350
California $141,590
Maryland $136,370
New Jersey $135,280
Massachusetts $131,750
Lowest medians
Mississippi $69,490
Louisiana $78,760
Puerto Rico $80,350
North Dakota $81,900
Alaska $84,110
State figures come from the 15-2051 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 70%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 0%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 48%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 10%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 0/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
21 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 81%
17 tasks
Medium exposure (≥ 35%) 14%
3 tasks
Low exposure (below 35%) 5%
1 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#16281 · Core · 77% automatable
Design and validate clinical databases, including designing or testing logic checks.
data analysis — Data quality profiling automated, human sets standards
Evaluate data quality. Create databases to store electronic data.
#16284 · Core · 82% automatable
Process clinical data, including receipt, entry, verification, or filing of information.
data analysis — Data preparation for analysis automatable
Evaluate data quality. Prepare data for analysis.
#16280 · Core · 70% automatable
Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.
data analysis — Diagnoses operational problems from data; human acts
Analyze data to identify or resolve operational problems.
#16285 · Core · 72% automatable
Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes.
text generation — AI drafts data management procedures; human approves
Develop procedures for data management.
#16279 · Core · 52% automatable
Monitor work productivity or quality to ensure compliance with standard operating procedures.
decision support — AI monitors logs; human owns operational compliance judgment
Monitor operational activities to ensure compliance with regulations or standard operating procedures.
#16268 · Core · 85% automatable
Prepare appropriate formatting to data sets as requested.
data analysis — Data preparation for analysis automatable
Prepare data for analysis.
#16286 · Core · 75% automatable
Design forms for receiving, processing, or tracking data.
text generation — AI drafts data entry procedures; human approves
Develop procedures for data entry or processing.
#16277 · Core · 75% automatable
Prepare data analysis listings and activity, performance, or progress reports.
data analysis — Analytical reports drafted; human validates analysis
Prepare analytical reports.
#16282 · Core · 55% automatable
Confer with end users to define or implement clinical system requirements such as data release formats, delivery schedules, and testing protocols.
interpersonal — Collaborative spec-setting requires human negotiation
Collaborate with others to determine design specifications or details.
#16278 · Core · 78% automatable
Perform quality control audits to ensure accuracy, completeness, or proper usage of clinical systems and data.
data analysis — Data quality profiling automated, human sets standards
Evaluate data quality.
#16283 · Core · 72% automatable
Analyze clinical data using appropriate statistical tools.
data analysis — Statistical analysis of health data; clinician verifies
Analyze health-related data.
#16269 · Core · 71% automatable
Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency.
decision support — Drafts sound recommendations; human validates against real systems
Evaluate utility of software or hardware technologies. Recommend changes to improve computer or information systems.
#16270 · Core · 70% automatable
Develop technical specifications for data management programming and communicate needs to information technology staff.
text generation — AI drafts data management procedures; human approves
Develop procedures for data management. Communicate project information to others.
#16273 · Core · 79% automatable
Write work instruction manuals, data capture guidelines, or standard operating procedures.
text generation — Draft instruction manuals from product details
Document operational procedures. Prepare instruction manuals.
#16274 · Core · 78% automatable
Track the flow of work forms, including in-house data flow or electronic forms transfer.
information retrieval — Collect archival data from sources
Collect archival data.
#16276 · Core · 32% automatable
Supervise the work of data management project staff.
interpersonal — IT staff supervision needs human judgment and accountability
Supervise information technology personnel.
#16272 · Core · 80% automatable
Contribute to the compilation, organization, and production of protocols, clinical study reports, regulatory submissions, or other controlled documentation.
text generation — Organize and check documentation accuracy largely automatable
Manage documentation to ensure organization or accuracy.
#16266 · Core · 80% automatable
Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.
information retrieval — AI scans trend sources; human weighs relevance
Update knowledge about emerging industry or technology trends.
#16275 · Core · 55% automatable
Train staff on technical procedures or software program usage.
interpersonal — Software training content AI-generatable, live coaching human
Train others in computer interface or software use.
#16271 · Supplemental · 62% automatable
Develop or select specific software programs for various research scenarios.
text generation — Design drafts aided; system architecture needs human judgment
Design software applications.
#16267 · Supplemental · 68% automatable
Provide support and information to functional areas such as marketing, clinical monitoring, and medical affairs.
text generation — Drafting project updates is AI-assisted; delivery is human
Communicate project information to others.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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