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Markets muddle through AI's uncertain revolution

Source: economist.com

TL;DR

Stockmarkets struggle to value AI because its economic impact remains unclear amid mixed signals.
Goldman Sachs index of AI-vulnerable firms fell more than 20% over the past year, while its AI-beneficiary index dropped nearly 5%.
History shows investors often misjudge tech revolutions, overrating some threats while underrating others.

The story at a glance

Markets find it hard to price AI's effects, just as they have with past technological shifts. The Economist examines conflicting signals, such as diverging share-price indices from Goldman Sachs and bond-market reactions to AI model releases. The piece appears now as AI hype persists but real-world productivity gains stay elusive. This echoes slower disruptions like those from earlier innovations.

Key points

Stockmarkets act as fortune-tellers, predicting firm profits, but falter when technologies upend old patterns—true for fast changes like crypto and slower ones like AI.
AI views in Silicon Valley split wildly: two technologists might give three answers on its world impact, leaving investors in the dark.[[1]](https://www.linkedin.com/posts/phillipose_why-investors-wont-know-what-to-make-of-activity-7439291731302383616-paq7)[[2]](https://www.linkedin.com/posts/songma_why-investors-wont-know-what-to-make-of-activity-7438027286756536320-Cr2N)
Goldman Sachs tracks firms most at risk from AI disruption; their share index dropped over 20% in the past year, even as broader markets hit highs.[[3]](https://www.livemint.com/ai/why-investors-won-t-know-what-to-make-of-ai-for-a-while-11773363902009.html)
The bank's mirror index of long-term AI winners, poised for productivity gains, has fallen nearly 5%.
Research by Maryam Farboodi shows long-term bond yields fell around major AI model releases, suggesting markets doubt big growth boosts.[[4]](https://mitsloan.mit.edu/faculty/directory/maryam-farboodi)
Song Ma of Yale finds analysts overestimate profits for firms with obsolete tech (gauged by patent freshness), propping up weak stocks.
AI progress is patchy—strong in coding, stalled in writing or ideas—while superintelligent AI profits are unknown amid high computing costs.

Details and context

AI looks like both a firm-killer and economy footnote, frustrating watchers. Markets reflect today's crowd wisdom, not future clarity. This fits history: new tech often sparks bubbles or dips as investors eye unlisted upstarts like OpenAI or Anthropic grabbing gains.[[2]](https://www.linkedin.com/posts/songma_why-investors-wont-know-what-to-make-of-activity-7438027286756536320-Cr2N)

Past revolutions took time to price right. AI adds extra fog: uneven advances across tasks and questions over who captures "artificial general intelligence" rents. Lower entry barriers could squeeze margins, especially with labs' soaring compute bills despite revenue jumps.

Analysts' blind spots amplify errors. Following Mr Ma's work, investors may overstate AI risks to some firms but miss threats to others. Bond moves hint at tempered growth hopes, not explosive change.

Key quotes

"Markets reflect only the collective wisdom of today’s investors. For as long as conversations between two Silicon Valley technologists produce three answers about AI’s impact on the world, no one will be the wiser."[[1]](https://www.linkedin.com/posts/phillipose_why-investors-wont-know-what-to-make-of-activity-7439291731302383616-paq7)

Why it matters

AI could reshape growth, profits, and risks, but markets' confusion signals high stakes in getting winners and losers right. Investors face churn: today's disrupted laggards may rebound, while apparent beneficiaries falter without clear edges. Watch earnings reports and AI adoption metrics for signs of real productivity, though full clarity may take years.