This is from the Goldman Sachs report “GEN AI: TOO MUCH SPEND, TOO LITTLE BENEFIT?”
Key Points from the Report:
- Investment Scale:
- Tech giants and other companies are projected to spend over $1 trillion on AI capital expenditures in the coming years, including investments in data centers, chips, AI infrastructure, and power grids[1][2].
- Skeptical Views:
- Daron Acemoglu (MIT): Acemoglu argues that the economic upside from AI over the next decade will be limited, predicting only a ~0.5% increase in productivity and ~1% increase in GDP. He believes that the transformative changes promised by generative AI will not happen quickly and will primarily enhance the efficiency of existing production processes rather than create new ones[1].
- Jim Covello (Goldman Sachs): Covello is skeptical about AI’s ability to solve complex problems that justify the high costs. He suggests that the expected decline in technology costs may not materialize as anticipated[1].
- Optimistic Views:
- Joseph Briggs, Kash Rangan, and Eric Sheridan (Goldman Sachs): These analysts are more optimistic about AI’s long-term economic potential. They believe that AI will eventually generate significant returns, even though its “killer application” has yet to emerge. They view the current phase as the “picks and shovels” stage, where foundational investments are being made[1][2].
- Constraints and Challenges:
- Chips and Power Shortages: The report also discusses potential constraints on AI growth due to the current semiconductor shortage (analyzed by Toshiya Hari) and a looming power shortage (discussed with Brian Janous from Cloverleaf Infrastructure)[1][2].
- Market Implications:
- Despite the concerns and constraints, the report suggests there is still room for the AI theme to develop, either through delivering on its promise or through prolonged investment cycles typical of technological bubbles[1][2].
Conclusion:
The Goldman Sachs report presents a balanced view on the future of AI investments, highlighting both the skepticism around immediate economic benefits and the optimism for long-term potential. The debate underscores the uncertainty in predicting the exact trajectory of AI’s impact on the economy and the importance of continued scrutiny and strategic investment[1][2][5].
Citations:
[1] https://www.goldmansachs.com/intelligence/pages/gs-research/gen-ai-too-much-spend-too-little-benefit/report.pdf
[2] https://www.goldmansachs.com/intelligence/pages/gen-ai-too-much-spend-too-little-benefit.html
[3] https://www.reddit.com/r/consulting/comments/1e0amhe/goldman_sachs_gen_ai_too_much_spend_too_little/
[4] https://news.ycombinator.com/item?id=40856329
[5] https://www.firstpost.com/tech/goldman-sachs-calls-genai-overhyped-wildly-expensive-warns-investor-of-ai-bubble-popping-soon-13793152.html