AI Adoption Gap Monitor - Stabilarity Hub

Overview

Sectors

Why? (XAI)

Signals

Velocity

Regional

Methodology

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Theoretical vs. observed coverage by sector

Baseline: Massenkoff & McCrory (2026), Anthropic Economic Index · Live: BLS JOLTS + GitHub + arXiv APIs

Sector breakdown with signal and mechanism

Occupation	Theoretical	Observed	Ratio	Rate/qtr	Signal	Mechanism
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Gap ratio = theoretical ÷ observed · Rate: estimated from BLS JOLTS + GitHub proxies

Explainable AI — what drives each sector's gap

Each gap is decomposed into four measurable factors with feature-importance weights. Click "Show breakdown" on any sector to see why the gap is the size it is — and what would need to change to close it.

XAI model: OLS regression on 6-sector baseline (Massenkoff & McCrory 2026). Four features: task routineness (O*NET), regulatory friction (EU AI Act risk tier), adoption lag (BLS tech adoption proxy), quality threshold (LLM benchmark error rate vs. sector tolerance). Low N = directional only. Feature weights show the proportional contribution of each factor to the observed gap. Positive = closes the gap, negative = widens it.

Feature weights: OLS on 6-sector dataset — low statistical power, treat as explanatory, not predictive

Labor market signals (BLS live)

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Developer adoption proxies (GitHub live)

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Declining hires rate + stable openings = substitution signal. Younger-worker hiring slowdown (Massenkoff & McCrory 2026) leads visible unemployment by 2–5 years. GitHub AI repo creation is the fastest-moving public proxy for developer-side adoption — strongest in Computer & Math, the sector with fastest gap closure.

BLS: api.bls.gov/publicAPI/v2 · Series LNS14000000, JTS*HIR, JTS*JOR · GitHub: api.github.com/search

Quarters to close — by sector

Sector	Observed	Ceiling	Gap	Rate/qtr	Quarters	Est. close
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Why velocity > gap size: A 60-pt gap closing at 5 pts/qtr resolves in 3 years. A 20-pt gap at 0.5 pts/qtr takes 10 years. Retraining programs and liability reforms have 2–5 year lead times. This table gives the actionable horizon.

March 2026 = baseline zero · Velocity estimated from public proxies — not official measurement

AI adoption gap by country — stability context

Countries with higher instability face larger AI adoption gaps due to regulatory uncertainty, infrastructure limitations, and capital flight. This table uses the Geopolitical Risk API to contextualize adoption barriers by country.

Country	Region	Stability Score	AI Adoption Likelihood	Gap Modifier
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Gap modifier logic: High instability (score > 0.6) = +30% gap expansion. Medium instability (0.3–0.6) = +15%. Stable (< 0.3) = baseline. Countries with regulatory uncertainty and infrastructure gaps face compounded adoption barriers — the theoretical-to-observed gap widens further.

Data: Geopolitical Risk API (/geo-risk-api/) · Weights: war 45%, political 35%, economic 20% · Updated: —

Data sources and limitations

Source	Measures	Freq	Limitation
BLS JOLTS	Job openings, hires, separations by sector	Monthly	2-month lag; broad NAICS only
BLS OES	Employment by detailed occupation	Annual	Annual only
GitHub API	AI/automation repo creation 2026	Real-time	Developer-heavy; enterprise often private
arXiv API	CS.AI paper volume 2026	Daily	Research ≠ deployment (6–24mo lag)
Anthropic baseline	Theoretical vs. observed (Mar 2026)	Periodic	Internal data — cannot replicate externally
Geo Risk API	Country stability scores (87 countries)	Real-time	Weighted composite; directional only

True observed exposure requires internal LLM usage logs. This monitor uses correlated public proxies for directional signal only. All data fetched client-side from free public APIs — no API keys, no server storage.

Anchor: Massenkoff, M. & McCrory, P. (2026). Labor market impacts of AI. Anthropic Economic Index. anthropic.com/research

Version: 1.3.0 | Last Updated: 2026-03-13 | Dependencies: Geo Risk API | Responsive: Mobile, tablet, desktop | Related Research: Capability–Adoption Gap

📡 API Dependencies

Geopolitical Risk API — /geo-risk-api/
Status: checking...
Endpoints used: /api/data/countries
Data: Country stability indices (87 countries), war/political/economic risk scores
Used for: Regional Analysis tab — contextualizing adoption gaps by country stability
If unavailable: Regional tab shows static reference data (10 key countries)
Check API status ↗

📋 Release Notes

v1.3.0 (2026-03-13)
• Full responsive redesign for mobile, tablet, and desktop
• Tabs now horizontally scrollable on mobile (no wrap)
• Metrics grid: 2-col on mobile/tablet, 4-col on desktop
• Tables wrapped in scrollable containers with touch optimization
• Floating "↑ Top" button for mobile long pages
• All touch targets: minimum 44px height
• Charts responsive with max-width:100%
• System fonts: -apple-system, system-ui, sans-serif
• Colors: strict palette (#000, #fff, #fafafa, #f5f5f5, #eee, #ddd, #555, #888)
• No border-radius, gradients, or box-shadows

v1.2.0 (2026-03-09)
• Added Regional Analysis tab — AI adoption gap by country using Geo Risk API
• Country stability scores contextualize adoption barriers
• Graceful fallback to static data if API unavailable

v1.1.0 (2026-03-08)
• Added XAI tab with feature importance breakdowns
• Added Velocity tab with quarters-to-close projections
• Chart.js visualizations

v1.0.0 (2026-03-06)
• Initial release: Overview, Sectors, Signals, Methodology tabs
• Anchor: Massenkoff & McCrory (2026) Anthropic Economic Index