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AI Automation Index
Will AI Replace Computer and Information Research Scientists?
Task-level automation exposure for Computer and Information Research Scientists: 15 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
59%
weighted task index
15 of 15 tasks scored
Median Salary
$140,300 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
37,200 people hold this job — size, not growth
Projected 2025–35
+21.8%
employment change
2,900 openings a year · BLS line item
Pay by state
BLS OEWS publishes 35 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$82,590 – $206,220
Highest medians
Oregon $206,220
Washington $202,400
New York $181,990
Massachusetts $170,510
New Mexico $165,690
Lowest medians
Michigan $82,590
Indiana $85,460
Georgia $92,250
Oklahoma $93,100
Utah $94,700
State figures come from the 15-1221 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 59%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 5%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 59%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
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 2/100
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
15 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) 47%
6 tasks
Medium exposure (≥ 35%) 53%
9 tasks
Low exposure (below 35%) 0%
0 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
#14623 · Core · 70% automatable
Analyze problems to develop solutions involving computer hardware and software.
data analysis — Diagnoses operational problems from data; human acts
Analyze data to identify or resolve operational problems.
#14626 · Core · 60% automatable
Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
decision support — AI advises on IT solutions; humans implement and validate
Apply information technology to solve business or other applied problems.
#14624 · Core · 68% automatable
Assign or schedule tasks to meet work priorities and goals.
decision support — Assignments drafted; accountability and negotiation human
Assign duties or work schedules to employees.
#14628 · Core · 62% automatable
Meet with managers, vendors, and others to solicit cooperation and resolve problems.
decision support — IT troubleshooting collaboration well-supported by AI
Collaborate with others to resolve information technology issues.
#14633 · Core · 50% automatable
Design computers and the software that runs them.
decision support — Integrated systems need human architecture and stakeholder judgment
Design integrated computer systems.
#14629 · Core · 82% automatable
Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
data analysis — Trend and relationship detection in data
Analyze data to identify trends or relationships among variables.
#14625 · Core · 55% automatable
Evaluate project plans and proposals to assess feasibility issues.
decision support — Design feasibility review aided, engineer owns judgment
Evaluate project designs to determine adequacy or feasibility.
#14635 · Core · 45% automatable
Participate in multidisciplinary projects in areas such as virtual reality, human-computer interaction, or robotics.
interpersonal — Research collaboration is iterative human teamwork
Collaborate on research activities with scientists or technical specialists.
#14627 · Core · 55% automatable
Consult with users, management, vendors, and technicians to determine computing needs and system requirements.
interpersonal — Collaborative spec-setting requires human negotiation
Collaborate with others to determine design specifications or details.
#14630 · Core · 58% automatable
Develop and interpret organizational goals, policies, and procedures.
text generation — Goals drafted; leadership accountability human
Develop organizational goals or objectives.
#14632 · Core · 70% automatable
Develop performance standards, and evaluate work in light of established standards.
data analysis — IT performance metrics well-suited to AI
Develop performance metrics or standards related to information technology.
#14634 · Supplemental · 54% automatable
Maintain network hardware and software, direct network security measures, and monitor networks to ensure availability to system users.
data analysis — AI monitors network performance via telemetry
Monitor the performance of computer networks. Maintain computer hardware.
#14637 · Supplemental · 44% automatable
Direct daily operations of departments, coordinating project activities with other departments.
decision support — AI coordinates cross-team plans; human resolves conflicts
Manage information technology projects or system activities. Coordinate project activities with other personnel or departments.
#14631 · Supplemental · 45% automatable
Participate in staffing decisions and direct training of subordinates.
interpersonal — Software training content AI-generatable, live coaching human
Train others in computer interface or software use. Participate in staffing decisions.
#14636 · Supplemental · 50% automatable
Approve, prepare, monitor, and adjust operational budgets.
decision support — Resource allocation tradeoffs need human judgment and authority
Manage budgets for appropriate resource allocation.
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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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