Barrie, ON · POP — · EMP 101,545 · DATA GRADE A

Barrie, ON

48.1 /100

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

#27 of 41

more exposed than 37% of Canadian CMAs

Secondary measures

19.5%

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 3,495 —
61.7
Retail and wholesale trade managers 2,700 —
68.2
Administrative officers 1,605 —
82.9
Elementary school and kindergarten teachers 2,425 —
46.9
Administrative assistants 1,140 —
94.9
Registered nurses and registered psychiatric nurses 1,995 —
43.3
General office support workers 1,040 —
74.2
Cashiers 1,725 —
41.9
Accounting and related clerks 800 —
86.6
Transport truck drivers 1,800 —
35.2

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

Compare Barrie against any other metro — side by side.