AI Transition – Run your own scenarios*
This tool is for discussion purposes only to understand the impact, timing, financial, and job impacts of AI to help understand the changes. We hope this will be used responsibly to start discussions on how to address what could be one of the largest impact on society since the industrial revolution.
AI Transition Scenario Calculator
Basic AI modeling tool to estimate how AI could change jobs, federal revenue, and the scale of UBI/UHI-style support over time.
Inputs
Outputs
AI Transition Scenario Calculator: What It Is and How to Use It
The AI Transition Scenario Calculator is a simple planning tool. It helps you explore how widespread AI adoption could affect three big things over the next 10-20 years:
- Jobs (how many roles could be displaced)
- US federal revenue (how tax receipts might change if the workforce changes)
- Support programs (the potential scale of UBI and UHI-style support)
This is not a prediction engine. It is a way to test “what if” scenarios and understand the size of possible change under different assumptions.
What the tool is doing (in plain terms)
The calculator starts with a timeline (start year and end year). Then it creates an “adoption curve” for AI – meaning AI spreads slowly at first, faster in the middle years, and then levels off.
From there, it estimates:
- How much of the job market is exposed to automation
- How strongly that exposure turns into net job displacement
- How job changes might affect federal revenue
- How large UBI (cash support) and UHI (health coverage support) costs could be if tied to displaced jobs
The charts let you hover over each year to see values and percentages.
How to use it
Step 1: Set the timeline
Pick the years you want to model. A common choice is 20 years (example: 2026 to 2046).
Step 2: Track 1 – AI adoption speed
- Midpoint year: when AI is roughly “half adopted” in your scenario
- Adoption speed (1-100): how fast the curve ramps up
- 1-25 = Low, 26-70 = Moderate, 71-100 = Severe
- Max adoption level: how high adoption gets by the end of your timeline
Step 3: Track 2 – Job impact
- Share of jobs that could be automated: long-run exposure
- How strongly AI replaces jobs (1-100): whether automation mostly changes tasks (low) or removes whole roles faster than new ones appear (high)
Step 4: Track 3 – Government response (money)
- Federal revenue as % of GDP: starting point for receipts
- How much displacement hurts revenue (1-100): how sensitive receipts are to job loss
- Ability to capture AI-era revenue: how well new mechanisms replace lost revenue
- UBI and UHI amounts: annual support per displaced person (model assumption)
Step 5: Run and compare scenarios
Click Run, then hover the charts year-by-year. Use Save/Load in the browser for quick testing, or Export/Import JSON to share scenarios.
Disclaimers
- This tool provides illustrative scenarios, not forecasts.
- It uses simplified relationships and does not model all economic feedback loops (inflation, interest rates, trade, migration, wars, policy shifts, business cycles, etc.).
- “Job displacement” here is an estimate of net roles affected, not a direct measure of unemployment.
- Results should be used for planning conversations, sensitivity testing, and education – not for personal financial decisions or policy design without deeper analysis.
- The Tax Project Institute is not an official Government agency
- Estimates are for illustrative purposes and not for official use.
