AI Automation Index

Will AI Replace Park Naturalists?

Task-level automation exposure for Park Naturalists: 20 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

46% weighted task index

20 of 20 tasks scored

Median Salary

$73,010 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

25,950 people hold this job — size, not growth

Projected 2025–35

+5.3% employment change

2,100 openings a year · BLS line item

Pay by state

BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$50,080 – $99,400

Highest medians

District of Columbia $99,400

Colorado $84,820

Maryland $83,290

Idaho $81,330

Wyoming $81,310

Lowest medians

Virgin Islands $50,080

Florida $51,130

South Carolina $52,310

Mississippi $59,510

Pennsylvania $61,480

State figures come from the 19-1031 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 46%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 9%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 54%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 8%

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 7/100 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

20 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) 17%

4 tasks

Medium exposure (≥ 35%) 61%

11 tasks

Low exposure (below 35%) 23%

5 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

#23960 · Core · 15% automatable

Provide care for park program animals.

visual inspection — Animal behavior observation is physical and situated

Monitor animal behavior or condition. Care for animals.

#3687 · Core · 55% automatable

Conduct field trips to point out scientific, historic, and natural features of parks, forests, historic sites, or other attractions.

information retrieval — Technical public assistance partly automatable; trust needs human

Provide technical information or assistance to public.

#3686 · Core · 55% automatable

Provide visitor services, such as explaining regulations, answering visitor requests, needs and complaints, and providing information about the park and surrounding areas.

information retrieval — Technical public assistance partly automatable; trust needs human

Provide technical information or assistance to public.

#3688 · Core · 55% automatable

Prepare and present illustrated lectures and interpretive talks about park features.

information retrieval — Technical public assistance partly automatable; trust needs human

Provide technical information or assistance to public.

#20866 · Core · 60% automatable

Plan and organize public events at the park.

decision support — Event planning drafts; logistics and vendors need humans

Plan special events.

#3691 · Core · 55% automatable

Assist with operations of general facilities, such as visitor centers.

information retrieval — Technical public assistance partly automatable; trust needs human

Provide technical information or assistance to public.

#24020 · Core · 45% automatable

Train staff and volunteers on park programs.

interpersonal — Job-skill training content AI-assisted; coaching human

Train personnel to enhance job skills. Instruct staff in work policies or procedures. Train staff members.

#3692 · Core · 40% automatable

Plan, organize and direct activities of seasonal staff members.

decision support — Operational planning drafted; execution accountability human

Plan work operations. Direct activities of subordinates. Supervise employees.

#20867 · Core · 50% automatable

Develop environmental educational programs and curricula for schools.

decision support — Drafts program outlines; institutional design and approval human

Develop educational programs.

#3690 · Core · 57% automatable

Confer with park staff to determine subjects and schedules for park programs.

data analysis — AI arranges schedules; human manages real-world changes

Schedule activities or facility use. Confer with others to conduct or arrange operational activities.

#3689 · Core · 11% automatable

Perform emergency duties to protect human life, government property, and natural features of park.

physical manipulation — Protection requires field work and enforcement in the world

Protect wildlife or natural areas. Protect property from fire or water damage. Provide first aid or rescue assistance in emergencies.

#3700 · Core · 40% automatable

Survey park to determine forest conditions and distribution and abundance of fauna and flora.

physical manipulation — Measuring environmental characteristics needs instruments

Measure environmental characteristics.

#3695 · Core · 69% automatable

Construct historical, scientific, and nature visitor-center displays.

visual inspection — Creates data graphics; accuracy and design review human

Design layout of art or product exhibits, displays, or promotional materials. Prepare graphics or other visual representations of information. Create images or other visual displays.

#3701 · Core · 59% automatable

Plan and develop audio-visual devices for public programs.

visual inspection — Creates data graphics; accuracy and design review human

Prepare graphics or other visual representations of information. Present information to the public.

#3699 · Core · 22% automatable

Take photographs and motion pictures for use in lectures and publications and to develop displays.

physical manipulation — Operating cameras at events is hands-on

Document events or evidence, using photographic or audiovisual equipment.

#3693 · Core · 13% automatable

Perform routine maintenance on park structures.

physical manipulation — Facility upkeep is hands-on physical work

Maintain facilities. Repair structural components.

#3694 · Core · 64% automatable

Prepare brochures and write newspaper articles.

text generation — Promotional copy and graphics largely AI; human approves

Develop promotional materials. Write articles, books or other original materials in area of expertise.

#3696 · Core · 50% automatable

Research stories regarding the area's natural history or environment.

information retrieval — Source synthesis aided; archival judgment and interpretation human

Conduct historical research.

#3698 · Supplemental · 78% automatable

Compile and maintain official park photographic and information files.

data analysis — Geographic data compilation, human checks quality

Compile geographic or related data.

#3697 · Supplemental · 30% automatable

Interview specialists in desired fields to obtain and develop data for park information programs.

interpersonal — Observation and interviews are inherently human

Collect information from people through observation, interviews, or surveys.

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Community Sentiment

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Method

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

See the full method →

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