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Kamloops, BC · POP — · EMP 54,155 · DATA GRADE A

Kamloops, BC

46.3 /100

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

#34 of 41

more exposed than 20% of Canadian CMAs

Secondary measures

17.5%

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

98.1%

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 2,110
61.7
Retail and wholesale trade managers 1,405
68.2
Administrative officers 800
82.9
Registered nurses and registered psychiatric nurses 1,395
43.3
Administrative assistants 600
94.9
Receptionists 615
84.5
Accounting technicians and bookkeepers 560
83.8
Social and community service workers 920
49.2
Cashiers 1,050
41.9
General office support workers 545
74.2

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

Compare Kamloops against any other metro — side by side.