# Foresters

> Manage public and private forested lands for economic, recreational, and conservation purposes. May inventory the type, amount, and location of standing timber, appraise the timber's worth, negotiate the purchase, and draw up contracts for procurement. May determine how to conserve wildlife habitats, creek beds, water quality, and soil stability, and how best to comply with environmental regulations. May devise plans for planting and growing new trees, monitor trees for healthy growth, and determine optimal harvesting schedules.

- **SOC code:** 19-1032.00
- **Canonical URL:** https://singulariki.com/roles/role-19-1032-00
- **Also known as:** Area Forester, Forester, Silviculturist, Timber Sales Administrator (Timber Sales Admin), District Forester, Fire Prevention Forester, Forest Practices Field Coordinator, Procurement Forester
- **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):
- Monitor contract compliance and results of forestry activities to assure adherence to government regulations.
- Negotiate terms and conditions of agreements and contracts for forest harvesting, forest management and leasing of forest lands.
- Plan and implement projects for conservation of wildlife habitats and soil and water quality.
- Establish short- and long-term plans for management of forest lands and forest resources.
- Procure timber from private landowners.
- Plan cutting programs and manage timber sales from harvested areas, assisting companies to achieve production goals.
- Determine methods of cutting and removing timber with minimum waste and environmental damage.
- Subcontract with loggers or pulpwood cutters for tree removal and to aid in road layout.
- Perform inspections of forests or forest nurseries.
- Map forest area soils and vegetation to estimate the amount of standing timber and future value and growth.
- Monitor forest-cleared lands to ensure that they are reclaimed to their most suitable end use.
- Supervise activities of other forestry workers.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Active Listening _(essential_skill)_
- Oral Comprehension _(ability)_
- Customer and Personal Service _(knowledge)_
- Reading Comprehension _(essential_skill)_
- Speaking _(essential_skill)_
- Critical Thinking _(essential_skill)_
- Complex Problem Solving _(transferable_skill)_
- Written Comprehension _(ability)_
- Oral Expression _(ability)_
- Deductive Reasoning _(ability)_
- Inductive Reasoning _(ability)_
- Information Ordering _(ability)_

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

**Tools & technology:**
- ESRI ArcGIS software _(hot technology, in demand)_
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft PowerPoint _(hot technology, in demand)_
- Microsoft Access _(hot technology)_
- Microsoft Active Server Pages ASP _(hot technology)_
- Microsoft Outlook _(hot technology)_
- Microsoft Word _(hot technology)_
- Geographic information system GIS systems _(in demand)_
- ESRI ArcView
- Forest Metrix
- Forest vegetation simulators

## AI exposure & outlook

- **AI task-overlap index:** 38th percentile (Moderate) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 43rd percentile (Moderate) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 59th percentile (Moderate) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 18th percentile (Low) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 6th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** no — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** 1.2% growth (About average); 1.1k annual openings; 13.8k → 14k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $70,660; 9,650 employed.

## 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/
- **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-19-1032-00_