Regina, SK · POP — · EMP 121,450 · DATA GRADE A

Regina, SK

51.4 /100

exposure score (OpenAI task-exposure index via NOC crosswalk — single-index tier)

#15 of 41

more exposed than 66% of Canadian CMAs

Secondary measures

25.3%

of workers are in occupations where ≥50% of tasks are LLM-exposed (Eloundou β; threshold-sensitive — note)

97%

of area employment matched to scored occupations (grade A)

Scenario: if replacement-level AI arrives in 2030

2027 2035

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

OccupationJobsMedian wageExposure [range]
Retail salespersons and visual merchandisers 4,475 —
61.7
Retail and wholesale trade managers 2,730 —
68.2
Administrative assistants 1,830 —
94.9
Administrative officers 1,885 —
82.9
Registered nurses and registered psychiatric nurses 3,080 —
43.3
Financial auditors and accountants 1,400 —
81.1
Information systems specialists 1,135 —
93.4
General office support workers 1,415 —
74.2
Elementary school and kindergarten teachers 2,165 —
46.9
Accounting and related clerks 1,085 —
86.6

Table 2. Ranked by exposure × local employment. Bands on the 0–100 occupation scale.

Compare Regina against any other metro — side by side.