U.S. annual real GDP growth (2030-2050) under AI progress scenarios

This market is conditional on selecting exactly one AI progress scenario (Slow, Moderate, or Rapid) based on public evidence by 2030-12-31. Moderators should use best judgment based on public benchmark results, deployment evidence, credible reporting, and observed capability demonstrations. If no scenario can be selected with sufficient confidence by the deadline, the market should close unresolved.

Slow Progress

By the end of 2030 in this slower-progress future, AI is a capable assisting technology for humans; it can automate basic research tasks, generate mediocre creative content, assist in vacation planning, and conduct relatively standard tasks currently performed by humans in homes and factories.

Researchers can get literature reviews on almost any topic at the level of a capable PhD student, but AI systems rarely produce novel and feasible solutions to difficult problems. Scientific breakthroughs remain mostly the result of human-run labs and grant cycles, though AI supports copy editing, data cleaning, and analysis.

AI can handle roughly half of freelance software-engineering jobs that would take an experienced human around 8 hours in 2025. AI-supported customer service can resolve most complaints. Writers get modest productivity boosts; short stories can be respectable, but long-form work still requires heavy human rewriting.

At home, an AI system can draft emails, top up grocery orders, collate news, and perform well-scoped tasks that would take a human about an hour or less. It can produce workable weeklong family-vacation itineraries and bookings. Self-driving improves but true level-5 systems do not yet exist. Home robots can make coffee and load/unload a dishwasher in some modern homes, but slower than most humans and with occasional guidance.

In advanced factories, autonomous systems can perform specific repetitive tasks requiring precision but little adaptability (for example wafer handling in semiconductor fabrication facilities).

Moderate Progress

By the end of 2030 in this middle-of-the-road future, AI is an effective collaborator across creative, corporate, and technical domains.

R&D teams can use autonomous lab systems with human assistants for rapid improvements in areas like solar-cell chemistries or fusion-reactor components, though advances are mostly incremental rather than revolutionary. Most freelance software-engineering jobs requiring up to 5 days of experienced-human effort can be handled by AI. Firms can replace most customer-service workflows with AI if customers accept AI service channels.

AI can draft 100,000-word novels good enough for mainstream 2025-style publication with normal editorial work, and can create 5-minute songs with breakout potential and quality comparable to top 2025 label releases. AI agents can manage weeklong travel plans end-to-end, including last-minute rebooking for weather or delays. Executive teams still lead companies, but can delegate multiday operational projects to agentic software.

Level-5 robo-taxis that can drive anywhere a human can finally exist. Home robots can navigate U.S. homes, make coffee, and load/unload dishwashers as fast and reliably as most humans, without guidance. In advanced factories, robots can adapt across tasks without extensive reprogramming and make real-time decisions with greater mobility.

Rapid Progress

By the end of 2030, AI systems are capable of competing with the best human minds and workers, and can surpass them.

Human leadership remains useful for high-level vision, but day-to-day execution can be delegated to AI systems. Autonomous researchers can compress years-long research timelines into days, weeks, or months, yielding game-changing technologies. Human freelancers are outperformed in software engineering and many service roles.

Creative systems can produce top-tier albums and prize-caliber novels, adapt those works into films, and execute commercialization workflows with minimal human oversight. Level-5 robo-taxis are widespread and materially safer than human drivers. General-purpose robots can robustly perform complex household and factory tasks at or above typical human speed and reliability.

Each yearly projection group resolves to annual U.S. real GDP growth for that calendar year using FRED series GDPC1 (source: U.S. Bureau of Economic Analysis): 100 * (GDPC1(Q1 Y) / GDPC1(Q1 (Y-1)) - 1), where Y is the group's year (2030 through 2050).

If BEA revises the series, use the latest revision available on the market resolution date. If GDPC1 is retired or renamed, use the most directly comparable BEA/FRED successor series.