Agentic Economy Simulator

AI-Driven Economic Transformation • 2026-2042

5x
$0
0.5%
0%
50%
2026
Simulation Year
🏦 Sovereign AI Fund Robot Tax → Citizen Ownership Transition
Robot Tax Revenue
$0.0T/yr
To AI Fund (50%)
$0.0T/yr
Fund Buys AI Equity
$0.0T total
Citizen Ownership
0.0%
Dividend per Citizen $0/yr
UBI Portion (to cash) $0.0T/yr
Autonomous Solvency 0%
Years to 50% Ownership
🏛️ Capital Ownership Model
Citizen Ownership
5%
Share of AI capital owned by workers/public
Capital Gains (Annual)
$0.0T
Total automation profits generated
Dividend Income
$0/yr
Per capita income from capital ownership
Autonomous Solvency
0%
% who can survive without wages (passive income)
🌍 Global Competition
World Avg Automation
20%
Global baseline (grows 3%/year)
Competitiveness Gap
-2%
Your automation vs world average
Export Penalty
0%
GDP drag from falling behind
Robot Tax Revenue
$0.0T
Automation tax → social fund
🛒 Aggregate Demand
100index
Wages + UBI relative to production capacity
💸 Fiscal Pressure
0%of GDP
UBI cost: $0T | Tax drag: 0%
⚖️ Demand-Supply Gap
0%gap
Negative = demand shortage (Henry Ford Paradox)
📉 Deflation Index
1.00price level
Tech deflation boosts real purchasing power
GDP & Effective Demand
Unemployment Rate (%)
Gini, Stress & Fiscal Pressure
Sector Automation Levels
Sector Analysis
SectorAutomationJobs (M)ProductivityNew JobsDisplacedNet
Event Log

Model Methodology & Documentation (v3.0)

How the Simulation Works

This simulator models the economic transformation driven by AI agents and automation technologies from 2024 to 2040. Version 3.0 introduces demand-side dynamics, fiscal constraints, and technological deflation based on critical feedback.

User Inputs
Scenario, Speed, UBI, Reskilling
Sector Dynamics
8 industries
Demand Engine
NEW: Consumption
Fiscal Model
NEW: UBI funding
Outputs
GDP, Employment

🆕 New in Version 3.0

🛒 Demand-Side Dynamics
GDP growth now constrained by aggregate demand. High unemployment reduces consumption, creating "Henry Ford Paradox" where robots produce but no one can buy. Formula: DemandGap = (Wages+UBI)/ProductionCapacity
💸 UBI Fiscal Reality
UBI now has real cost calculated as % of GDP. High UBI creates tax burden that slows investment and automation. Creates balancing feedback loop previously missing.
📉 Technological Deflation
Automation reduces prices (deflationary pressure). Lower prices increase real purchasing power even with lower nominal wages. Price index tracks this effect.
🎚️ Adjustable Unemployment Cap
Can now model extreme scenarios (25%/35%/50% caps). Previous 25% hard limit prevented seeing worst-case "Doomsday" scenarios.

📋 Available Scenarios

⚖️ Baseline α = 8%
Current trajectory with moderate automation growth. Represents continuation of present trends without major policy interventions or technological breakthroughs.
Agent: 12%Reskill Eff: 15%Friction: 20%
🚀 Accelerated α = 20%
Rapid AI advancement with aggressive corporate adoption. Minimal regulation, strong investment. Fastest growth but highest disruption and inequality risk.
Agent: 35%Reskill Eff: 10%Friction: 5%
🎯 Managed α = 10%
Coordinated transition with strong safety nets. High reskilling investment, UBI programs. Balances innovation with social stability.
Agent: 18%Reskill Eff: 35%Friction: 15%
🛡️ Resistance α = 4%
Strong labor protection and regulatory barriers. Heavy AI taxation, employment quotas. Preserves jobs but limits productivity gains.
Agent: 6%Reskill Eff: 8%Friction: 50%
🏛️ Cooperative α = 12%
Worker-owned automation model. High capital ownership (35%), moderate robot tax. Workers receive dividends as robots replace wages - solving demand crisis through market mechanisms rather than government transfers.
Ownership: 35%Robot Tax: 5%UBI: $12k

Core Mathematical Models

1. Automation Diffusion (S-Curve)
dρ/dt = κ · α · ρ · (1 - ρ/ρmax) · (1 - f) · (1 - τ/2)
ρ=automation, κ=speed, α=base rate
f=friction, τ=tax burden (NEW: UBI funding slows investment)
2. Aggregate Demand
D = (W · E + UBI · Pop) · (1 + δ)
W=avg wage, E=employed (M)
UBI=transfer amount, Pop=population
δ=deflation boost to purchasing power
3. GDP with Demand Constraint
geff = gbase · min(1, D/Y) · (1 - τ·0.3)
gbase=productivity-driven growth
D/Y=demand/supply ratio (Henry Ford factor)
τ=fiscal drag from UBI taxation
4. Fiscal Pressure
τ = (UBI · Pop · 330M) / (GDP · $28T)
UBI cost as fraction of GDP
Creates negative feedback: high UBI → high taxes → slower investment
5. Technological Deflation
Pt+1 = Pt · (1 - 0.02 · ρ̄)
Prices fall ~2% per 100% automation
δ = (1/P) - 1 = purchasing power boost
6. Social Stress (Enhanced)
σ = 0.2 + 2u + 2(G-0.35) + σch - UBIeff + τ·0.5
Now includes fiscal pressure stress
High taxes to fund UBI create political tension

Sector Parameters

Sectorρ₀ρₘₐₓμJobsNotes
🏭 Manufacturing25%85%2.512.5MHigh automation potential
🛒 Retail20%75%2.015.5ME-commerce driven
🏦 Finance30%80%3.06.8MAlready digitized
🏥 Healthcare10%45%1.820.5MHuman-centric
🚛 Logistics15%90%2.810.2MAutonomous vehicles
💼 Professional12%60%2.214.0MAI assistants
🎓 Education8%35%1.59.5MHuman essential
🤖 Technology20%50%4.05.5MHighest multiplier

📖 Glossary of Key Concepts

🛒 Aggregate Demand
Total purchasing power in the economy from wages and transfers. When demand falls below production capacity, GDP growth stalls regardless of productivity (Henry Ford Paradox: robots produce but unemployed can't buy). This addresses the critical demand-side gap in economic modeling.
Demand = (Wages × Employed + UBI × Population) × Deflation
💸 Fiscal Pressure
UBI cost as percentage of GDP. High UBI requires high taxes, which slow corporate investment and automation adoption. Creates the negative feedback loop missing from simpler models: UBI helps demand but hurts supply-side investment.
0-10%: Sustainable 10-20%: Straining 20%+: Critical
📉 Technological Deflation
Automation reduces production costs, lowering prices over time. This increases real purchasing power even if nominal wages fall. A key mechanism allowing populations to survive technological transition - goods become cheaper faster than incomes fall.
Real GDP = Nominal GDP × (1/Price Index)
⚖️ Demand-Supply Gap
Difference between aggregate demand and production capacity. Negative gap = demand shortage: factories can produce more than people can afford to buy. This constrains GDP growth regardless of productivity - the mathematical proof of why UBI matters.
>0%: Demand sufficient -10% to 0: Mild shortage <-10%: Demand crisis
📈 S-Curve (Logistic Growth)
Mathematical model of technology diffusion. Adoption starts slow (innovators), accelerates rapidly (mass market), then plateaus (saturation). The formula captures this: growth is proportional to both current adoption and remaining potential. Based on Bass (1969) and Rogers' Diffusion of Innovations.
dρ/dt = κ · α · ρ · (1 - ρ/ρmax) · (1 - friction)
📊 Gini Coefficient
Standard measure of income/wealth inequality (0-1). Zero = perfect equality, One = one person owns everything. Automation increases Gini (capital owners capture gains), while UBI and reskilling reduce it by redistributing benefits.
0.25-0.35: Nordic levels 0.35-0.45: US current >0.45: Instability risk
🔥 Social Stress Index
Composite indicator (0.1-0.95) of societal tension from unemployment, inequality, pace of change, and fiscal pressure. High stress reduces tech acceptance, slows innovation, and risks social unrest. Also includes fiscal stress - high taxes for UBI create political backlash even if economically necessary.
0.1-0.4: Stable society 0.4-0.7: Growing tension >0.7: Crisis/unrest risk
⚡ Productivity Index
Economic output per unit of input, indexed to 100 in base year (2024). Automation boosts productivity through AI efficiency gains. Each sector has a multiplier (μ) determining how much productivity each automation point delivers. Technology sector: μ=4.0, Education: μ=1.5.
Π = 100 × (1 + ρ × μ × 0.1)
🤖 Tech Acceptance Rate
Population percentage viewing AI/automation positively (starts 65%). Evolves based on social stress: successful transitions increase acceptance, while job losses decrease it. Higher acceptance → faster automation adoption, lower regulatory friction. Creates reinforcing loop.
↑ Low stress, visible benefits ↓ High unemployment, rapid displacement
🌐 Economic Inclusivity
Measure (0.3-0.95) of how broadly automation gains are shared. Low inclusivity = benefits concentrate among tech owners and high-skilled workers. Influenced inversely by Gini, positively by reskilling and UBI. Higher inclusivity → sustainable growth, social stability.
I = 0.72 - (G-0.39)×0.5 + R×0.3 + UBI×0.15
💡 Innovation Index
Multiplier (1.0-3.0) for economy's capacity to create new industries and jobs. Higher automation and tech acceptance fuel innovation. Affects new job creation: more innovation means automation creates proportionally more new roles (AI trainers, robot supervisors, prompt engineers).
Innovation = 1 + ρ×1.5 + (tech-0.5)×0.5
💰 Universal Basic Income (UBI)
Unconditional cash transfers to all citizens ($0-$36,000/yr). Directly reduces Gini (redistribution) and stress (economic security). Unlike welfare, no work disincentive cliff. Note: high UBI creates fiscal pressure that slows automation investment.
Gini: -0.08 at max Stress: -0.20 at max Demand: ↑ supports consumption
🎓 Reskilling Programs
Government workforce retraining (% of GDP). Helps displaced workers transition to new economy jobs. Effectiveness varies by scenario (8%-35% efficiency). Model note: 50% reintegration rate is optimistic - real structural unemployment may be stickier.
Unemployment: direct reduction Gini: -0.05 per 1% GDP Inclusivity: enables mobility
⚙️ Automation Rate (ρ)
Fraction of sector tasks performed by AI/robots (0-100%). Each sector has initial level (ρ₀) and maximum potential (ρmax). Logistics: 90% max (autonomous vehicles), Education: 35% max (human essential). Higher automation → productivity gains + job displacement.
30%: Early automation 50%: AI-augmented economy 70%+: Near full automation
🔄 Feedback Loops
Circular cause-effect chains where outputs become inputs. Reinforcing (R): automation→productivity→profits→investment→more automation. Balancing (B): automation→unemployment→stress→regulation→slower automation. Understanding loops predicts non-linear behavior.
R: Productivity spiral ↑↑ B: Social constraint ↓↑
📉 Regulatory Friction (f)
Dampening factor (0-50%) representing how regulation slows automation. Varies by scenario: Accelerated (5%) = deregulation, Resistance (50%) = strong labor protection. Effective growth = base × (1-f). Note: Tax drag from UBI adds implicit friction.
Accelerated: 5% Managed: 15% Baseline: 20% Resistance: 50%
🏛️ Worker Ownership
Percentage of AI/automation capital owned by workers or public (0-50%). Through ESOPs, cooperatives, sovereign wealth funds, or tokenized equity. When workers own the robots, they receive dividends instead of just wages - solving the "who buys the products?" problem without government transfers.
Gini: -0.25 at 100% ownership Stress: -0.30 buffer (psychological) Demand: ↑ via dividends
💎 Capital Gains & Dividends
Automation generates ~30% of GDP×automation_rate in capital profits annually. Worker ownership entitles workers to proportional dividends. At 35% worker ownership and 50% automation, this yields ~$15,000/person/year in passive income - potentially replacing wages entirely.
Dividend = (GDP × ρ × 0.3 × ownership%) / population
🎯 Autonomous Solvency
Percentage of population that can survive on passive income alone (dividends + robot tax transfers) without wages or government UBI. This is the "post-work" readiness metric. At 100%, society has achieved true economic freedom from labor - the end goal of the cooperative scenario.
0-25%: Traditional economy 25-50%: Transition phase >50%: Post-scarcity signals
🤖 Robot Tax
Tax on automation profits (0-30%) redistributed to population. Alternative to UBI - funded by capital rather than general taxation. Reduces Gini and funds social programs, but creates some investment drag. Can offset UBI fiscal burden when both are used together.
Gini: -0.10 at 30% Funds UBI without income tax Investment drag: ~50% of rate
🌍 Global Competition
World average automation grows ~3%/year from 20% baseline. If your economy falls >10% behind, export competitiveness suffers and GDP growth is penalized. This creates external pressure to automate regardless of domestic social concerns - the "race to the bottom" dynamic.
>+5%: Competitive advantage ±5%: Parity <-10%: Export penalty active

Theoretical Foundations

Demand-Side Economics
Keynes (1936) "General Theory" - Aggregate demand determines output; supply doesn't create its own demand.
Henry Ford Paradox
Ford's insight that workers must afford products they make. Automation without redistribution collapses demand.
Technological Deflation
Rifkin "Zero Marginal Cost Society" (2014) - Technology drives prices toward zero, fundamentally changing economics.
Capital Ownership Models
Piketty (2014), Varoufakis "Another Now" (2020) - Broad-based capital ownership as alternative to wealth concentration.
Worker Cooperatives
Mondragon Corporation model, Platform Cooperativism movement - Employee ownership at scale.
Robot Taxation
Bill Gates (2017), EU Parliament debates - Taxing automation to fund social programs.
UBI Fiscal Analysis
Widerquist (2018) "Cost of Basic Income" - Net cost analysis considering tax recapture.
System Dynamics
Sterman "Business Dynamics" (2000) - Feedback loops, stocks/flows for complex system modeling.