Gini Loh System Tools

AI Automation Index

Will AI Replace Switchboard Operators, Including Answering Service?

Task-level automation exposure for Switchboard Operators, Including Answering Service: 19 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified
Developed & audited by Gini Loh

Automation Exposure

48% weighted task index

19 of 19 tasks scored

Median Salary

$38,630 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

34,280 people hold this job — size, not growth

Projected 2025–35

-26.0% employment change

3,100 openings a year · BLS line item

Pay by state

BLS OEWS publishes 47 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$24,960 – $59,860

Highest medians

Hawaii $59,860
District of Columbia $54,700
California $48,840
Washington $47,800
Minnesota $47,430

Lowest medians

Puerto Rico $24,960
Mississippi $30,520
Alabama $32,210
Texas $33,620
South Carolina $34,010

State figures come from the 43-2011 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 48%

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

Physical work 30%

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

Judgment & influence 28%

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

Routine administration 22%

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 4/100 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

19 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) 44%

9 tasks

Medium exposure (≥ 35%) 15%

3 tasks

Low exposure (below 35%) 41%

7 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

#4630 · Core · 30% automatable

Operate communication systems, such as telephone, switchboard, intercom, two-way radio, or public address.

physical manipulation — Operating comms hardware needs hands-on setup and tuning

Operate communications equipment or systems.
#4631 · Core · 72% automatable

Answer incoming calls, greeting callers, providing information, transferring calls or taking messages as necessary.

interpersonal — Call routing automatable; nuanced calls need human

Answer telephones to direct calls or provide information.
#20431 · Core · 43% automatable

Greet visitors, log them in and out of the facility, assign them security badges, and contact employee escorts.

decision support — Routing referrals from criteria; human confirms fit

Refer customers to appropriate personnel. Greet customers, patrons, or visitors.
#20430 · Core · 64% automatable

Monitor emergency and code alarms, make emergency announcements, or route emergency calls to the appropriate location.

interpersonal — Call routing automatable; nuanced calls need human

Monitor alarm systems. Answer telephones to direct calls or provide information.
#4640 · Core · 20% automatable

Record messages, suggesting rewording for clarity or conciseness.

physical manipulation — Recording equipment physically set up and operated

Operate audio recording equipment.
#4633 · Core · 30% automatable

Page individuals to inform them of telephone calls, using paging or interoffice communication equipment.

physical manipulation — Operating comms hardware needs hands-on setup and tuning

Operate communications equipment or systems.
#4634 · Core · 60% automatable

Relay or route written or verbal messages.

interpersonal — Relaying information needs real-time human channel

Relay information between personnel.
#20432 · Core · 33% automatable

Perform various cash handling tasks, such as collecting payments, making bank deposits, or managing petty cash.

physical manipulation — Handling cash/payment collection in person

Prepare cash for deposit or disbursement. Collect deposits, payments or fees.
#4635 · Core · 30% automatable

Place telephone calls or arrange conference calls as instructed.

physical manipulation — Operating comms hardware needs hands-on setup and tuning

Operate communications equipment or systems.
#20428 · Core · 12% automatable

Process incoming or outgoing mail, packages, or deliveries.

physical manipulation — Sorting physical mail requires hands-on handling

Sort mail.
#20427 · Core · 87% automatable

Perform various data entry or word processing tasks, such as updating phone directories, typing or proofreading documents, or creating schedules.

text generation — Proofreading text for accuracy is core LLM strength

Proofread documents, records, or other files to ensure accuracy. Type documents.
#20429 · Core · 68% automatable

Perform administrative tasks, such as accepting orders, scheduling appointments or meeting rooms, or sending and receiving faxes.

decision support — Calendar scheduling automatable; exceptions need human judgment

Schedule appointments. Execute sales or other financial transactions.
#4637 · Supplemental · 55% automatable

Monitor alarm systems to ensure that secure conditions are maintained.

decision support — AI can triage alarms; human verifies and responds physically

Monitor alarm systems.
#4638 · Supplemental · 8% automatable

Contact security staff members when necessary, using radio-telephones.

situated mobility — Physical security presence in world

Maintain security.
#4643 · Supplemental · 68% automatable

Complete forms for sales orders.

text generation — Compliance docs drafted; human owns regulatory accuracy

Prepare documentation for contracts, transactions, or regulatory compliance.
#4642 · Supplemental · 68% automatable

Answer simple questions about clients' businesses, using reference files.

information retrieval — Product questions answered from knowledge base

Answer customer questions about goods or services.
#4641 · Supplemental · 45% automatable

Stamp messages with time and date and file them appropriately.

physical manipulation — Filing physical documents requires hands in the world

File documents or records.
#4639 · Supplemental · 85% automatable

Keep records of calls placed and charges incurred.

data analysis — Maintain call records in structured systems

Maintain call records.
#20433 · Supplemental · 75% automatable

Place orders, such as for equipment, supplies, or catering for meetings.

decision support — Ordering via systems automatable; human approves spend

Order materials, supplies, or equipment.
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Community Sentiment

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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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