Goldman Sachs' Joseph Briggs: Gen AI could lift U.S. labor productivity 15% in 10 years

Core Insights - The article discusses the significant increase in AI spending by major companies like Apple, Meta, and Alphabet, with total capital expenditure (capex) reaching $116 billion, leading to discussions about a potential bubble in the market [1] - Goldman Sachs economist Joseph Briggs argues that this level of spending is sustainable and compares the current investment climate to historical infrastructure investments in railroads and telecom [2][3] Group 1: AI Spending Analysis - Current AI spending in the US is slightly below 1% of GDP, which is not unprecedented compared to historical infrastructure investments that typically reached 2-5% of GDP [3] - The annualized AI spending rate is estimated to be between $250 billion and $300 billion, with indications that it may already be surging above $300 billion based on recent earnings reports [8] - The expectation is that AI investment could eventually reach around 2% of GDP, with current spending levels indicating that the industry is halfway to this target [5][6] Group 2: Productivity and Economic Impact - Full adoption of AI is projected to lead to a 15% increase in labor productivity, which could create significant economic value estimated at around $8 trillion [10] - Current adoption rates of AI in production are low, with only 10% of companies reporting regular use, indicating that the macroeconomic impact has yet to be realized [11][12] - Initial boosts to GDP from AI are forecasted to begin in 2027, gradually increasing into the 2030s, with potential impacts on job growth already observed in the tech sector [13][14]