Headline risk
34%
High RiskExecutive Assistant
This page reuses the same role shell as Singapore, but the component occupations are mapped onto the United States layer so the score, context, and support bundle reflect US public evidence.
Why this score
81% of tasks overlap with current AI
42% human advantage from judgment & presence
66% demand buffer from the local labour market
These factors combine multiplicatively — larger bars do not mean proportionally larger contributions to the final score.
Weighted overlap across component occupations
Human coordination and physical presence protection
Blended local-market buffer for this role
Component coverage and mapping quality
Workflow profile
Heuristic workflow context blended from the role mix. This explains the score; it is not used as a direct local-market forecast.
Workflow dimensions (0 = low, 1 = high)
United States support
Evidence bundle
Weighted task overlap from O*NET statements and Anthropic penetration
Median annual wage from BLS OEWS
Employment projections and openings from BLS
Preparation and entry requirements from O*NET and BLS
Support snapshot
Job zone
2The occupation usually needs some preparation before entry.
Median wage
USD 37,230USD 32,660 to USD 44,070
Openings
128.5K0.0% projected change
Median age
36.81.2M employed
Occupation profile
Answer inquiries and provide information to the general public, customers, visitors, and other interested parties regarding activities conducted at establishment and location of departments, offices, and employees within the organization.
Job Zone 2 · Some preparation
The occupation usually needs some preparation before entry.
Task primitives
Matched task weight share: 100% · Effective coverage: 32%
Concentration: 25%
Wage context
Median annual
USD 37,230
Mean annual
USD 38,480
Hourly median: USD 18
Employment: 964,530 workers
10th percentile: USD 28,280
90th percentile: USD 48,870
Demand outlook
2024 employment
1007.2K
2034 employment
1007.6K
Openings: 128.5K
Projected change: 0.0%
Education: High school diploma or equivalent
Work experience: None
On-the-job training: Short-term on-the-job training
Median wage in projections: USD 37,230
Employment of receptionists is projected to decline 0 percent from 2024 to 2034.
Requirements and friction
Telework: 2.7% · Telework: 97.3% · Credentials: <5%
Narrative and skills
Receptionists do tasks such as answering phones, receiving visitors, and providing information about their organization to the public.
Receptionists are employed in nearly every industry.
Receptionists typically need a high school diploma or equivalent and good communication skills.
The median hourly wage for receptionists was $17.90 in May 2024.
Employment of receptionists is projected to decline 0 percent from 2024 to 2034.
Jobs: 1,007,200
Median pay: USD 37,230
Employment outlook: Employment of receptionists is projected to decline 0 percent from 2024 to 2034.
Openings: 300
Tasks and tools
- 1. Operate telephone switchboard to answer, screen, or forward calls, providing information, taking messages, or scheduling appointments. · AI use 100%
- 2. Greet persons entering establishment, determine nature and purpose of visit, and direct or escort them to specific destinations. · AI use 0%
- 3. Transmit information or documents to customers, using computer, mail, or facsimile machine. · AI use 0%
- 4. File and maintain records. · AI use 0%
- 5. Hear and resolve complaints from customers or the public. · AI use 100%
- 6. Provide information about establishment, such as location of departments or offices, employees within the organization, or services provided. · AI use 0%
Work context
- Telephone Conversations: 5.0/5
- Contact With Others: 4.9/5
- Frequency of Decision Making: 4.6/5
- E-Mail: 4.5/5
- Face-to-Face Discussions with Individuals and Within Teams: 4.4/5
- Indoors, Environmentally Controlled: 4.3/5
Tech density
6/6
6 hot · 4 in demand
Work pace
4.6/5
Average of the strongest work-context signals.
Worker profile
Median age: 36.8
Total employed: 1.2M · Under 25: 22% · 25 to 54: 56% · 55+: 21%
Support note
Built from O*NET occupation descriptions, task statements, technology skills, work context, Job Zones, Anthropic task penetration, BLS OEWS wages, BLS projection tables, BLS ORS requirements, BLS OOH narrative content, BLS skills data, and BLS CPS occupation age tables.
Source vintage
O*NET 30.2 / OEWS 2024 / ORS 2025 / OOH 2025-08-28 / Projections 2024-34 / CPS 2025 / Anthropic task penetration
Component occupations
Methodology
Shared spine
structural_pressure = exposure × (1 - bottleneck)
Country layer
headline_risk = structural_pressure × (1 - country_demand_resilience)
Published limitations
This is a synthetic role view built from mapped occupations. It reuses the same shell and visual components as the Singapore role pages, but only the US sources that actually exist are rendered here.