911 Dispatcher
Structural exposure score derived from 2 independent sources (OpenAI "GPTs are GPTs" (human_rating_beta) + AIOE (Felten, Raj & Seamans)), each normalized against its own full reference population and combined by simple average, then converted to a percentile.
In real usage data, AI shows up in this job more often than in most occupations.
Technical detail
Based on Microsoft's "Working with AI" study of real Copilot conversations mapped to O*NET tasks (arXiv 2507.07935): Public Safety Telecommunicators scored 0.346 on AI applicability, notably above the cross-occupation mean (0.159, stdev 0.098) across all 785 SOC codes studied — banded here as High real-world AI usage relative to other occupations.
Corroborating signal from the Anthropic Economic Index (Claude.ai/API conversations, a different product and userbase than the Microsoft data above): Public Safety Telecommunicators shows measurable Claude usage tied to this occupation's tasks, though at low absolute volume — treat as directional confirmation, not a second precise score.
What a 911 dispatcher actually does
911 dispatchers — officially titled public safety telecommunicators — answer emergency calls, determine what's happening and where, and decide which police, fire, or EMS units to send, often while the caller is still in danger.
On a medical call, dispatchers trained in Emergency Medical Dispatch (EMD) protocols stay on the line to walk a caller through CPR, childbirth, or hemorrhage control until responders arrive — a standard practice since the late 1980s that requires a specifically trained person on the other end of the line, not just call routing.
Dispatchers work from a structured but flexible script: triaging call priority in seconds, cross-referencing addresses and caller history in the CAD (computer-aided dispatch) system, coordinating simultaneously with multiple responding units, and keeping a caller calm enough to give usable information during the worst moment of their day.
Shifts run around the clock in 24/7 communication centers, frequently with mandatory overtime during short-staffed shifts, and the job carries a documented risk of secondary traumatic stress from repeated exposure to callers' worst emergencies.
Some AI tools are now used to screen and de-duplicate non-emergency and lower-priority calls before they reach a dispatcher, freeing them to focus on genuine emergencies — but every deployment found treats this as call-volume triage support, not a substitute for the licensed telecommunicator who takes the actual emergency call. Entry requires a high school diploma, completion of state-mandated telecommunicator training (commonly 40+ hours), and, in most states, passing a certification exam within the first year of employment.
Why it reads this way
911 Dispatcher scores lowest of anyone in this batch on the numeric structural exposure score (12/100) yet carries an above-average real-world AI usage signal — a distinction worth stating plainly rather than smoothing over. Real deployment backs that signal up: New Orleans became the first major US city, in 2026, to deploy AI (vendor Carbyne) to help triage and de-duplicate incoming 911 calls, with Seattle and Atlanta reportedly exploring similar tools.
But every documented deployment remains explicitly assistive — flagging and organizing calls for a human dispatcher, not replacing the person who answers the phone, gives real-time pre-arrival instructions (CPR coaching, guiding an unassisted childbirth, talking a caller through a structure fire), and carries the legal and safety responsibility for those decisions.
That live, two-way, high-stakes verbal interaction with a caller who is often panicked or hard to understand is the core of the job, and it isn't something these tools attempt to take over. Entry requirements are comparatively light — a high school diploma, 40+ hours of telecommunicator training, and a state or APCO certification exam — a weaker legal wall than most jobs on this site, which is part of why the numeric score reads this low.
Nationwide reporting instead documents a persistent, worsening 911-dispatcher staffing shortage, not a surplus created by automation. This occupation also scores meaningfully lower than its emergency-services peers (firefighter, paramedic, police officer): dispatch work is more verbally and data-mediated (call-taking, protocol lookup, CAD data entry) and less physically embodied than on-scene response, a real structural distinction rather than an inconsistency — and the reason this page carries an accelerated review given how actively this specific niche is moving.
Skills this role draws on
We don't yet have task-by-task time-share data for this occupation, so we can't show which specific tasks carry the exposure score above. This is the real skill set instead.
Typical salary range (USD)
$35,640–$78,110
Average: $54,800/yr
Range source: BLS Occupational Outlook Handbook, May 2024 (Median Annual Wage)
Average source: BLS Occupational Employment and Wage Statistics, May 2024 (Annual Mean Wage, SOC 43-5031)
Related careers
Head-to-head comparisons
As of 2026-08-10, 911 Dispatcher scores 12/100 on structural exposure — the lowest numeric score in this batch — but is the only job in it with a High Microsoft usage-data band (0.346 AI applicability, notably above the cross-occupation mean), a real signal that deserves honest disclosure rather than being outweighed by the low headline score. Category 1 evidence is genuinely live and commercial-scale: New Orleans deployed AI (vendor Carbyne) in 2026 to triage and de-duplicate 911 calls, with Seattle and Atlanta reportedly exploring similar tools — more concrete deployment than any other job in this batch. Every deployment found, however, is explicitly assistive: it flags/organizes calls for a human dispatcher, who still takes the call, delivers real-time pre-arrival life-safety instructions, and carries the legal responsibility. Category 2 is weak (HS diploma, 40+ training hours, a certification exam — a genuinely light credentialing wall, consistent with the low headline score rather than offsetting it). Category 3 is strong: live two-way emergency communication with a distressed caller, split-second triage judgment, and legal accountability for dispatch decisions. Cross-check flag: this occupation scores far below its Safe-verdict emergency-services peers (firefighter 88, paramedic 73, police officer 69) — explained by dispatch work being more verbally/data-mediated and less physically embodied than on-scene response, a real structural distinction, not an oversight. Net verdict: AI-resistant despite the paperwork, Medium confidence, with an accelerated review given this is the most actively-moving AI-adoption niche found in this batch.
This is a researched judgment (checklist v1.2), not a statistical measurement — it sits alongside, not instead of, the structural exposure signal above. Next scheduled review: 2027-02-10.
Sources (5)
- https://www.bls.gov/ooh/office-and-administrative-support/police-fire-and-ambulance-dispatchers.htm
- https://www.onetonline.org/link/summary/43-5031.00
- https://www.newsweek.com/new-orleans-ai-911-calls-other-cities-12303090
- https://carbyne.com/ai-powered-911-emergency-call-triage-that-thinks-with-you/
- https://wisconsinwatch.org/2026/02/who-you-gonna-call-wisconsin-911-dispatchers-discuss-fixes-to-national-statewide-shortage/
Data sources & methodology
Salary data: BLS Occupational Outlook Handbook, May 2024 (Median Annual Wage). Min/max figures represent the 10th–90th percentile annual wage range across the United States. Average figure sourced separately: BLS Occupational Employment and Wage Statistics, May 2024 (Annual Mean Wage, SOC 43-5031).
Automation Risk Score: Based on O*NET occupational analysis (43-5031.00) evaluating task complexity, physical requirements, social intelligence, and environmental variability. Methodology based on research from Frey & Osborne (Oxford, 2017).
Growth projections: 3% (2024-2034), based on BLS Occupational Outlook Handbook.