What the model outputs. For a profession–country pair, the model returns $T_{50}$ — the median-like horizon (years) until AI/robots can perform roughly 50% of total task-time of that job in that country (at current adoption pace).
| Key | Meaning | Default |
|---|---|---|
GAIrate | Gen‑AI progress multiplier (digital channel) | 1.00 |
GRPrate | Robotics progress multiplier (physical channel) | 1.00 |
| Key | Meaning |
|---|---|
Digit | Digitization of workload |
StdTsk | Task standardization / repeatability |
DataAcc | Data availability / accessibility |
Decmp | Decomposability into micro-tasks |
ErrTol | Error tolerance / detectability |
Remot | Remote-friendly work share |
EcoStm | Economic incentive (wages/shortages) |
PhysCt | Physical contact / manipulation |
MobReq | Mobility / on-site logistics |
EnvVar | Environmental variability |
Licns | Licensing / regulation |
CapEx | Capital intensity for automation |
DigShare | Share of inherently digital tasks |
HAS | Human approval steps (1–5 scale) |
Trust | Stakeholder trust in machine output |
CustPrf | Customer preference for a human agent |
| Key | Meaning |
|---|---|
CTAIdig | Digital AI availability/adoption |
CTAIphy | Robotics capability/availability |
LabEqRt | Labor cost ratio |
TechFrz | Capital freeze / fleet stasis |
OrgInrt | Organizational inertia |
SocRes | Social/cultural resistance |
GovBrak | Political/regulatory brakes |
MktCmp | Market competition |
MigOffs | Migration offset (personal) |
Two unit scores are computed from profession factors (weights sum to 1.00 in each block):
Digital amenability: $$ S = 0.22\,Digit + 0.18\,StdTsk + 0.12\,DataAcc + 0.12\,Decmp + 0.12\,ErrTol + 0.14\,Remot + 0.10\,EcoStm. $$
Physical/organizational friction: $$ F = 0.30\,PhysCt + 0.15\,MobReq + 0.12\,EnvVar + 0.18\,Licns + 0.25\,CapEx. $$
Base horizon (years): $$ T_{\text{base}} = T_0 \cdot e^{\,F - S}, \quad T_0=4.0. $$
Approvals and trust act multiplicatively (fewer approvals / higher trust → faster):
$$ \text{Agency} = \exp(-\gamma\,(HAS-3))\,\cdot\,\exp\!\left(-\lambda\,\Big(\tfrac{Trust+CustPrf}{2}-0.5\Big)\right), $$
with clamps to \([0.70,1.30]\), $\gamma=\ln(1.25)/2$, $\lambda=\ln(1.25)/0.5$.
Physical branch uses the full country brake: $$ \text{Common}_{phy} = \dfrac{\sqrt{SocRes\,\cdot\,GovBrak}}{MktCmp^{0.7}}. $$
Digital branch attenuates country frictions for highly digital jobs (DigShare close to 1):
$$ k_d = 0.5\,(1 - DigShare^2),\; k_m = 0.7\,(1 - DigShare^2), \quad \text{Common}_{dig} = \dfrac{(SocRes\,\cdot\,GovBrak)^{\,0.5\,k_d}}{MktCmp^{\,k_m}}. $$
Digital availability (clamped near 1 for cross-country parity), organizational drag and result:
$$ CTAI^{eff}_{dig} = (1-w)\cdot 1 + w\cdot \operatorname{clip}(CTAI_{dig};\,0.92,1.08),\; w=(1-DigShare)^{1.35}. $$
$$ \text{drag}_{dig} = OrgInrt^{\,1 - DigShare^{1.5}},\quad T_{dig} = \dfrac{T_{base}\cdot \text{drag}_{dig}\cdot \text{Common}_{dig}\cdot Agency}{GAIrate\cdot CTAI^{eff}_{dig}}. $$
Physical availability, economic freeze and result:
$$ CTAI^{eff}_{phy} = \min\!\left(1,\; \dfrac{CTAI_{phy}}{1+0.35\,\ln(LabEqRt)}\right),\quad Freeze = \dfrac{1}{\max(1-TechFrz,\;0.25)}. $$
$$ T_{phy} = \dfrac{T_{base}\cdot OrgInrt^{0.8}\cdot \text{Common}_{phy}\cdot Freeze \cdot Agency}{GRPrate\cdot \sqrt{CTAI^{eff}_{phy}}}. $$
If $TechFrz\ge0.80$, $LabEqRt\ge3$, $CTAI_{phy}\le0.15$: clamp $T_{phy}\in[20,35]$.
Weight the channels (emphasize digital as DigShare grows), apply migration offset and a global cap:
$$ w_{dig}=DigShare^{1.2},\quad T_{50} = \min\!\big(\,(w_{dig} T_{dig} + (1-w_{dig}) T_{phy}) \cdot MigOffs,\; 35\,\big). $$
Digit/DigShare and higher approvals.