Gini Loh System Tools

AI Automation Index

Will AI Replace Telemarketers?

Task-level automation exposure for Telemarketers: 12 O*NET tasks scored against their work activities, plus the simulator.

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Developed & audited by Gini Loh

Automation Exposure

67% weighted task index

12 of 12 tasks scored

Median Salary

$35,450 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

58,430 people hold this job — size, not growth

Projected 2025–35

-21.4% employment change

5,800 openings a year · BLS line item

Pay by state

BLS OEWS publishes 42 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$21,540 – $48,010

Highest medians

Kansas $48,010
Colorado $47,670
California $46,000
Connecticut $45,200
Massachusetts $44,650

Lowest medians

Mississippi $21,540
North Dakota $23,440
Oklahoma $26,880
Pennsylvania $28,430
Puerto Rico $28,580

State figures come from the 41-9041 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 67%

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

Physical work 0%

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

Judgment & influence 11%

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

Routine administration 30%

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 0/100 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

12 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) 71%

9 tasks

Medium exposure (≥ 35%) 29%

3 tasks

Low exposure (below 35%) 0%

0 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

#4619 · Core · 45% automatable

Contact businesses or private individuals by telephone to solicit sales for goods or services, or to request donations for charitable causes.

interpersonal — Outreach scripts drafted; live customer contact is human

Contact current or potential customers to promote products or services.
#4621 · Core · 82% automatable

Obtain customer information such as name, address, and payment method, and enter orders into computers.

data analysis — Maintain structured customer account records

Maintain records of customer accounts.
#4620 · Core · 62% automatable

Explain products or services and prices, and answer questions from customers.

information retrieval — Product questions answered from knowledge base

Explain technical product or service information to customers. Answer customer questions about goods or services.
#4622 · Core · 82% automatable

Record names, addresses, purchases, and reactions of prospects contacted.

data analysis — Maintain structured customer account records

Maintain records of customer accounts.
#4627 · Core · 82% automatable

Maintain records of contacts, accounts, and orders.

data analysis — Maintain structured customer account records

Maintain records of customer accounts.
#4625 · Core · 72% automatable

Answer telephone calls from potential customers who have been solicited through advertisements.

interpersonal — Call routing automatable; nuanced calls need human

Answer telephones to direct calls or provide information.
#4618 · Core · 50% automatable

Deliver prepared sales talks, reading from scripts that describe products or services, to persuade potential customers to purchase a product or service or to make a donation.

interpersonal — Slides drafted; live delivery and persuasion are human

Deliver promotional presentations to current or prospective customers.
#4626 · Core · 45% automatable

Telephone or write letters to respond to correspondence from customers or to follow up initial sales contacts.

interpersonal — Outreach scripts drafted; live customer contact is human

Contact current or potential customers to promote products or services.
#4623 · Supplemental · 75% automatable

Adjust sales scripts to better target the needs and interests of specific individuals.

text generation — Generates sales content drafts; human tailors and approves

Develop content for sales presentations or other materials.
#4624 · Supplemental · 68% automatable

Obtain names and telephone numbers of potential customers from sources such as telephone directories, magazine reply cards, and lists purchased from other organizations.

data analysis — AI analyzes market data to identify prospects

Identify potential customers.
#4628 · Supplemental · 70% automatable

Schedule appointments for sales representatives to meet with prospective customers or for customers to attend sales presentations.

interpersonal — Prospect scheduling involves persuasion and relationship

Schedule appointments with prospective customers.
#4629 · Supplemental · 80% automatable

Conduct client or market surveys to obtain information about potential customers.

information retrieval — AI aggregates and analyzes market data at scale

Monitor market conditions or trends.
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Community Sentiment

Do you agree?

Do you agree with the AI automation risk score calculated for this occupation?

Method

How this was scored

  1. 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
  2. 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. 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. 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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