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Telemarketers

Sales & Marketing
Projected change 2024–34: -22.1%
Median annual wage (2024): $34,410
Employment (2024): 67K

United States · BLS Employment Projections 2024–34 (figures for SOC 41-9041 occupational group)

AI exposure in published research

Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.

Data provider: OpenAI · "GPTs are GPTs"

Time basis: 2023 baselineex-ante estimate

Scored against GPT-4-generation capability.

Human rater basis
52.8%
GPT-4 rater basis
80.6%

β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.

12 rated tasks · 12 tasks with β ≥ 0.5 (100.0%)

Version:
gh-main-0471612
License:
MIT License · Copyright (c) 2024 OpenAI

Data provider: Anthropic Economic Index

Time basis: Published 2026-03-05composite index

Observed exposure
28.5%

Theoretical exposure index weighted by measured Claude usage, per the original report's definition.

12 tasks · usage observed in 4 · mean 33.0%

Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex

AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

Version:
hf-lmi-2026-03
License:
CC BY 4.0
Observation period:
(not applicable to this release)
Model:
(not stated by the source)

2023 prediction vs observation-based index published 2026-03-05

One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.

Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.

The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.

The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.

These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.

Task Breakdown

  • Make outbound sales calls
  • Read scripted sales pitches
  • Log call outcomes in CRM
  • Handle customer objections

About This Occupation

If you work as a Telemarketer, AI is reshaping your profession. With an automation risk of 76/100 and overall exposure at 78%, this role faces very high transformation. The highest-impact area is read scripted sales pitches at 92% automation. This is classified as an 'automate' role. BLS projects -22% decline through 2034. Workers in this field should urgently explore transitioning to roles requiring complex interpersonal skills.

ISCO-08 classification

Unit group 5244ILO official

Contact Centre Salespersons

Definition

ILO original text (English)

Contact centre salespersons contact existing and prospective customers, using the telephone or other electronic communications media, to promote goods and services, obtain sales and arrange sales visits. They may work from a customer contact centre or from non-centralised premises.

Definition & vocabulary source

Source: International Labour Organization (ILO) — ISCO-08 Structure

License: ILO CC BY 4.0

View original

Official occupational information

  • ONET41-9041.00

    Telemarketers

    Solicit donations or orders for goods or services over the telephone.

    View original

Source: O*NET 30.2, U.S. DOL/ETA

License: CC BY 4.0

View original

Frequently Asked Questions

The Anthropic Economic Index puts observed exposure at 28.5%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 52.8% under human raters. Both figures are reproduced from published research without modification.

They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.

No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.