AI Advancement Could Boost U.S. GDP by Nearly Half by 2030

Without coordinated governance, he warned

Anthropic co-founder Jack Clark warned that rapidly improving artificial intelligence will accelerate change across all sectors, speaking at the IMF and World Bank annual meetings on Saturday. He emphasized that international cooperation is essential to establish effective rules for AI development and deployment. Clark noted that one of Anthropic’s internal models projects a potential increase in U. S. economic output of almost 50% by 2030 under certain conditions, highlighting both the transformative promise and risks of unmanaged AI progress. How AI Could Reshape Economic Growth Clark explained that advances in AI capabilities are not incremental but exponential, enabling breakthroughs in productivity, scientific research, and industrial automation. He stressed that realizing these gains depends on creating global frameworks that prevent misuse while encouraging innovation.

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Without coordinated governance, he warned, the benefits of AI could be unevenly distributed or undermined by safety risks, geopolitical tensions, or ethical failures. What Safeguards Are Needed to Harness AI Responsibly? The Anthropic co-founder called for shared standards on AI safety, transparency, and accountability across nations, similar to agreements in other high-impact technologies. He pointed out that unilateral actions by individual countries could lead to regulatory arbitrage or technological fragmentation. Clark urged institutions like the IMF and World Bank to facilitate dialogue between governments, tech firms, and civil society to build trust and align incentives for responsible AI advancement. Frequently Asked Questions What specific conditions would allow AI to boost U. S. GDP by nearly 50% by 2030?

Clark referenced Anthropic’s internal modeling

Clark referenced Anthropic’s internal modeling, which assumes sustained progress in AI capabilities combined with effective adoption across industries and supportive policy environments, though he did not disclose the exact thresholds or variables used in the forecast. Why does Clark stress international cooperation over national AI strategies? He argued that AI’s global impact—spanning supply chains, labor markets, and security—requires coordinated rules to prevent race-to-the-bottom dynamics, ensure safety, and maximize broad-based economic gains rather than enabling competitive fragmentation. How soon might policymakers see tangible effects from AI-driven economic shifts? Clark suggested that while long-term projections like the 2030 GDP estimate are model-based, near-term impacts are already visible in areas such as software development, logistics, and customer service, with acceleration expected as models become more capable and accessible.