Tucson, AZ · POP 1,074,685 · EMP 389,630 · DATA GRADE A
Tucson, AZ
consensus exposure · range [49.8–50] across 6 methodologies
more exposed than 78% of US metros
By methodology
| Index | Exposure |
|---|---|
| OpenAI task exposure (Eloundou et al. 2024) | 49.9 |
| Felten language-modeling AIOE (2023) | 50.0 |
| Microsoft AI applicability (2025) | 49.9 |
| Anthropic Economic Index observed usage (2026) | 49.8 |
| Eisfeldt et al. generative-AI exposure (2024) | 49.8 |
| Consensus (mean) | 49.9 |
Table 1. Where indices disagree, that disagreement is information: prediction-style indices (task ratings) and usage-based indices (observed AI conversations) measure different things. Methods §2.
Secondary measures
payroll-weighted exposure — higher than the headcount number: the exposed jobs are the better-paid ones
of workers are in occupations where ≥50% of tasks are LLM-exposed (Eloundou β; threshold-sensitive — note)
of area employment matched to scored occupations (grade A)
Scenario: if replacement-level AI arrives in 2030
Figure 1. Modeled displacement under the median preset (diffusion k=0.8, ceiling 0.75, automation share 0.45, friction lag 1.5y, attrition 3%/y). Solid: positions eliminated. The gap between gross and layoffs is natural attrition — speed of diffusion, not depth of exposure, determines layoffs. This is a scenario, not a forecast: adjust every assumption.
Where the losses land — and your assumptions
Positions eliminated by 2035 per occupation group, under the arrival year selected above. Drag any multiplier if you think we're wrong about a group — your model, your numbers. Multipliers scale that group's task exposure (×0 = immune, ×2 = double).
Table 3. Group exposure = employment-weighted mean task exposure (Eloundou β) over the group's local occupations. Bars use the same scenario engine as Figure 1 (median preset).
Most exposed local occupations
| Occupation | Jobs | Median wage | Exposure [range] | |
|---|---|---|---|---|
| Retail Salespersons | 11,100 | $34,530 | 67 | |
| Customer Service Representatives | 7,880 | $40,090 | 91.1 | |
| General and Operations Managers | 12,130 | $83,610 | 56.5 | |
| Office Clerks, General | 8,070 | $43,920 | 82.2 | |
| Cashiers | 9,610 | $32,780 | 54.8 | |
| Registered Nurses | 10,120 | $94,110 | 48.9 | |
| Software Developers | 4,060 | $123,710 | 87.1 | |
| Secretaries and Administrative Assistants, Except Legal, Medical, and Executive | 3,630 | $45,030 | 89.8 | |
| Waiters and Waitresses | 7,300 | $36,490 | 39.7 | |
| First-Line Supervisors of Office and Administrative Support Workers | 3,500 | $59,440 | 79.3 |
Table 2. Ranked by exposure × local employment. Bands on the 0–100 occupation scale.
Compare Tucson against any other metro — side by side.