# Cost Estimators

> Prepare cost estimates for product manufacturing, construction projects, or services to aid management in bidding on or determining price of product or service. May specialize according to particular service performed or type of product manufactured.

- **SOC code:** 13-1051.00
- **Canonical URL:** https://singulariki.com/roles/role-13-1051-00
- **Also known as:** Construction Estimator, Cost Analyst, Cost Estimator, Estimator, Acquisition Cost Estimator, Analyst, Cost Consultant, Cost Engineer
- **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):
- Analyze blueprints and other documentation to prepare time, cost, materials, and labor estimates.
- Confer with engineers, architects, owners, contractors, and subcontractors on changes and adjustments to cost estimates.
- Collect historical cost data to estimate costs for current or future products.
- Assess cost effectiveness of products, projects or services, tracking actual costs relative to bids as the project develops.
- Consult with clients, vendors, personnel in other departments, or construction foremen to discuss and formulate estimates and resolve issues.
- Prepare estimates used by management for purposes such as planning, organizing, and scheduling work.
- Prepare estimates for use in selecting vendors or subcontractors.
- Establish and maintain tendering process, and conduct negotiations.
- Set up cost monitoring and reporting systems and procedures.
- Review material and labor requirements to decide whether it is more cost-effective to produce or purchase components.
- Prepare cost and expenditure statements and other necessary documentation at regular intervals for the duration of the project.
- Conduct special studies to develop and establish standard hour and related cost data or to reduce cost.

**Emerging tasks** (O*NET):
- Use remote sensing technologies or drones to evaluate site conditions when in-person visits are not feasible.

## Skills, tools, capabilities

**Knowledge, skills & abilities** (O*NET, highest importance first):
- Mathematics _(knowledge)_
- Inductive Reasoning _(ability)_
- Reading Comprehension _(essential_skill)_
- Mathematics _(essential_skill)_
- Oral Comprehension _(ability)_
- Oral Expression _(ability)_
- Mathematical Reasoning _(ability)_
- Economics and Accounting _(knowledge)_
- Speaking _(essential_skill)_
- Written Comprehension _(ability)_
- Number Facility _(ability)_
- Active Listening _(essential_skill)_

**Skills in demand:**
- Mathematics _(Common Skill)_
- Inductive Reasoning _(Common Skill)_
- Reading Comprehension _(Common Skill)_
- Deductive Reasoning _(Common Skill)_
- Critical Thinking _(Common Skill)_
- Active Listening _(Common Skill)_
- Information Ordering _(Specialized Skill)_
- Writing _(Common Skill)_
- Microsoft Outlook _(Common Skill)_
- Microsoft Excel _(Common Skill)_
- Complex Problem Solving _(Common Skill)_
- Speech Recognition _(Specialized Skill)_

**Tools & technology:**
- Microsoft Excel _(hot technology, in demand)_
- Microsoft Office software _(hot technology, in demand)_
- Microsoft Outlook _(hot technology, in demand)_
- Adobe Acrobat _(hot technology)_
- Autodesk AutoCAD _(hot technology)_
- Autodesk Revit _(hot technology)_
- Intuit QuickBooks _(hot technology)_
- Microsoft Access _(hot technology)_
- Microsoft PowerPoint _(hot technology)_
- Microsoft Project _(hot technology)_
- Microsoft Visio _(hot technology)_
- Microsoft Word _(hot technology)_

## AI exposure & outlook

- **AI task-overlap index:** 95th percentile (High) across all occupations — composite of current-era exposure studies (ai-exposure-index-v1).
- **Overall AI exposure (Felten et al.):** 94th percentile (High) — source: felten_aioe.
- **LLM task exposure, γ (OpenAI / Eloundou):** 95th percentile (High) — source: eloundou_gamma.
- **AI assistant applicability (Microsoft):** 81st percentile (High) — source: microsoft_applicability.
- **Frey–Osborne (2013, historical computerization estimate):** 49th percentile — kept separate from current-era studies.
- **Remote-capable (Dingel–Neiman):** yes — task structure, not who actually works remote.
- **Projected employment (BLS 2024–34):** -4.2% growth (Declining); 16.9k annual openings; 221.4k → 212.1k jobs.
- **Pay & employment (BLS OEWS, May 2024):** median $77,070; 219,530 employed.

## How people actually use AI here

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

- **Automation vs augmentation:** 18% automation, 39% augmentation (usage-weighted).
- **Autonomy median:** 3.8 (higher = AI acts more independently).
- **Dominant collaboration mode:** task iteration.

**Tasks most handed to AI here:**
- Consult with clients, vendors, personnel in other departments or construction foremen to discuss and formulate estimates and resolve issues. _(0.7% of measured AI use; task iteration)_
- Assess cost effectiveness of products, projects or services, tracking actual costs relative to bids as the project develops. _(0.5% of measured AI use; task iteration)_

**Example prompts (honest phrasings of the tasks above — starting points, not endorsed instructions):**
- Help me consult with clients, vendors, personnel in other departments or construction foremen to discuss and formulate estimates and resolve issues.
- Help me assess cost effectiveness of products, projects or services, tracking actual costs relative to bids as the project develops.

## 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-13-1051-00_