The most immediate AI milestone is not singularity, but "Economic AGI," where AI can perform most virtual knowledge work better than humans. This threshold, predicted to arrive within 12-18 months, will trigger massive societal and economic shifts long before a "Terminator"-style superintelligence becomes a reality.

Stripe data shows the median top AI company operates in 55 countries by its first year, double the rate of SaaS companies from three years prior. This borderless nature from day one requires financial infrastructure that can immediately support global payment methods and compliance.

Patrick Collison suggests AI fundamentally changes software economics. Instead of a fixed-cost product sold at scale, software will become bespoke, created on-demand for individual users at the moment of consumption, similar to ordering a custom pizza. This introduces variable inference costs.

Elon Musk theorizes that if 'applied intelligence' is a direct proxy for economic growth, the exponential advancement of AI could lead to unprecedented double-digit GDP growth within 18 months and potentially triple-digit growth in five years. This frames AI not just as a tool, but as the primary driver of a new economic golden era.

Stanford economist Erik Brynjolfsson argues that a major downward revision of 2025 job numbers, while GDP figures remained strong, mathematically implies a massive productivity surge. This suggests AI's economic impact is finally visible in macroeconomic data, moving beyond anecdote and theory.

Despite widespread adoption, Patrick Collison notes that AI has not yet produced measurable gains in macroeconomic productivity. He points to recent studies and the lack of corresponding GDP growth outside the U.S. as evidence that the diffusion of these technologies through the economy is slow and complex.

Sam Altman suggests that as AI models create enormous economic value, proxy metrics like task completion benchmarks will become obsolete. The most meaningful chart will be the model's direct impact on GDP. This signals a fundamental shift from the research phase of AI to an era of broad economic transformation.

The true economic revolution from AI won't come from legacy companies using it as an "add-on." Instead, it will emerge over the next 20 years from new startups whose entire organizational structure and business model are built from the ground up around AI.

General-purpose technologies like AI initially suppress measured productivity as firms make unmeasured investments in new workflows and skills. Economist Erik Brynjolfsson argues recent data suggests we are past the trough of this "J-curve" and entering the "harvest phase" where productivity gains accelerate.