Retirement Overview
KPI cockpit for retirement readiness — fiscal, healthspan & AI leverage.
Snapshot synthesizes core pressure gauges, cross-check guardrails, and a Quadratic Map to keep retirement policy moves tied to real-world constraints.
Data scope: UN DESA WPP 2022 · World Bank · WHO · OECD (regionally aggregated).
Currently viewing: Global
Region view · Global
Sustainability Gap
Workers per Retiree
Healthy Years Post-Ret
AI Labor Lift
Global aggregates derived from UN DESA WPP 2022, World Bank WDI, WHO GHO, and OECD/World Bank productivity indices (normalized).
Fiscal & Labor Cross-Checks
- On-track
Pay-as-you-go coverage
95% contribution capture; leakage <1.2% of payroll.
- Watchlist
Capital buffer ratio
Funded pillar at 18% of GDP; goal 22% by 2030.
- On-track
Labor force participation 55–64
69% participation after incentives; +3ppt YoY.
Healthspan & Equity Cross-Checks
- Watchlist
Preventable morbidity
Down 9% since 2015; cardio & metabolic gaps remain.
- On-track
Care economy capacity
1.8M trained caregivers; AI support pilots scaling.
- On-track
Low-income protection
Income-tested boost covers bottom 35% of retirees.
Quadratic Map
Impact × Feasibility of next-wave plays
Bubble size = expected 2035 fiscal/health benefit score. Use to pressure-test prioritization before funding rounds.
AI-driven concept brief
AI Upskilling Credits
Boosts older-worker employability by tying tax credits to AI-enabled training completions; pairs well with automation lift KPI.
Topic masterclass
Frame AI as a universal productivity layer, then target mid-career cohorts with modular nanodegrees, union-backed upskilling, and outcome-based credits.
Execution levers
- Link AI certification registries to payroll withholding for instant tax relief.
- Deploy sector academies (health, logistics, public admin) with shared datasets.
- Track re-employment speed and wage deltas to prove ROI to finance ministries.
Hover any bubble to refresh the AI explanation and align policy moves with readiness data.
AI policy copilot
AI Analysis & Recommendations
In Global, the sustainability gap lives at -0.9% GDP with 3.6× workers supporting each retiree. Healthspan extends to 6.3 yrs, while automation promises +8.5% uplift—enough raw material for a decisive, consultancy-grade modernization push.
Playbook cadence · Quarterly policy sprints · Executive storyboard ready
Fiscal runway
Ahead of glide-path. +0.6 ppt vs 2020.
Support ratio
Stable support ratio. +0.2 vs 2020.
Healthy retirement window
Healthspan momentum. +0.4 yrs vs 2015.
Automation tailwind
High automation upside. Scenario-weighted 2030.
Action playbook
Channel automation savings into pension buffers
+8.5% effective labor lift can be earmarked to push the funded pillar above the 22% of GDP target while the gap sits at -0.9% GDP. Use rolling AI productivity audits to capture the gains and automatically divert a share into sovereign funds.
Scale flexible retire-plus participation
With 3.6× workers per retiree, nudging older workers into part-time AI-supported roles keeps the ratio above 3.5× even if growth slows. Anchor participation goals into civil-service performance contracts and offer ergonomic retrofits to employers hitting return-to-work milestones.
Accelerate healthspan prevention pods
6.3 yrs of healthy years post-retirement plus the +0.4 year gain indicates prevention pilots work—fund more cardio-metabolic and fall-prevention cohorts to lock in gains. Blend AI triage, tele-coaching, and social prescribing so pods stand up within six months.
Orchestrate a McKinsey-grade transformation office
Stand up a central AI policy PMO that tracks the above plays, issues fortnightly heatmaps, and unblocks procurement. Pair every policy lever with a CXO-level sponsor and a data-driven KPI tree so ministers can course-correct mid-quarter.