Richard Socher Analyzes Reasons Why AI Progress Has Not Led to Significant GDP Growth
Former Salesforce Chief Scientist Richard Socher stated that despite significant advancements in AI, there are three main reasons why GDP has not exploded: AI only replaces partial processes, slow adoption by businesses; AI-native startups need time to establish go-to-market strategies; and more importantly, many core economic sectors do not rely on high intelligence, such as tourism, real estate, luxury goods, food supply chains, sports entertainment, and mining, which will not fundamentally change even if intelligence becomes cheap.
He believes that knowledge work, research-intensive industries, and the digital economy will benefit the most and surpass traditional industries.
Market Mechanism: AI dividends are concentrated in knowledge and deep technology fields, with funds shifting from traditional low-intelligence industries to high-productivity digital economies, slowing growth in traditional industries while accelerating expansion in the new economy.
Source: Public Information
ABAB AI Insight
As a senior expert in the AI field, Richard Socher, who previously led projects like Salesforce Einstein, emphasizes the gradual transformation of the real economy by AI. Traditional industries are constrained by physical and human limitations, while knowledge work will be the first to explode.
In terms of capital pathways, funds like a16z are focusing on AI-native companies and deep technology, directing resources towards scalable digital products, motivated by capturing the productivity leap dividends and strategically building new economic growth points that surpass traditional GDP measurements.
Currently, we are in the early stages of industry restructuring despite the maturity of AI technology, and the knowledge economy will lead the next round of expansion.
Structural Judgment: Essentially, this is a capital concentration driven by technological substitution. AI makes intelligence cheaper, but changes in industries constrained by physical realities are slow. Capital is concentrating on knowledge-intensive new economies, with the mechanism being the reshaping of industry weight through productivity enhancement, achieving a structural transition from traditional physical economies to digital knowledge economies.
ABAB News · Law of Cognition
- Cheap intelligence does not equal reconstruction of everything; the physical world still has hard constraints.
- Traditional GDP low-intelligence sectors remain stable, while the knowledge economy will quietly surpass.
- AI changes what can be changed, leaving what cannot be changed; that is the real world.