Continuing the AI theme.

▪️Share of companies that actively used AI in the last 6 months, by US economic sector:

• Information services – 45-50%
• Professional and business services – 35-40%
• Finance – 25-30%
• Education and healthcare – 20-25%
• Wholesale trade – 15-20%
• Utilities – 12-15%
• Manufacturing – 10-15%
• Retail trade – 10-15%
• Construction – 5-10%
• Other services – 5-10%
• Hospitality/leisure – 5%
• Transportation – 5%
• Agriculture – 3-5%
• Mining – 3-5%.

The data are not final, rather at an early stage of adoption, i.e., the share of companies will continue to grow.

This distribution allows us to assess which sectors are susceptible to potential labor displacement from AI and which sectors may be affected by AI transformation in terms of productivity, cross-sectoral connectivity, and margins.

▪️The IMF modestly emphasizes that AI could contribute to rising unemployment on a trajectory of accelerated AI adoption, which aligns with my hypothesis that the speed of AI development and adoption may be many times faster than the economy's ability to adapt, creating 'sinister' gaps in employment and productivity between sectors.

Labor adaptation, retraining, and cross-sectoral morphing (merging and layering of industries, e.g., finance, IT, and business consulting as a single entity) have significant inertia, which will inevitably provoke imbalances (some segments super-marginal, others in deep crisis).

▪️AI carries risks of widening the gap between poor and rich countries, including on the trajectory of technological singularity and accelerated growth of innovation and technological progress in AI application points (I added this on my own in addition to the IMF narrative).

▪️The gap may widen not only among countries but also among economic sectors due to redistribution of cash (capital) flows, trade flows, labor, and margin levels, creating priority and depressed industries in the investment profile (again added on my own, developing logic partially touched but not expanded by the IMF).

▪️Expansion of AI infrastructure (primarily data centers) creates additional pressure on the energy market, which is especially relevant in the context of the Middle East energy shock. Realizing the benefits of AI requires:

• Expansion of electricity generation capacity;
• Scaling of critical intermediate resources (chips, rare earth elements, etc.), with rare earth materials almost entirely dependent on China (double political risk).

▪️The IMF once again warns of possible irrational resource reallocation in the economy due to excessive expectations from AI, where the channels of impact from AI disappointment could be:

1. Decline in AI sector investment;
2. Collapse of technology company stocks;
3. Negative wealth effect → slowdown in consumption;
4. Blow to export economies (Taiwan, Korea, Vietnam, etc.) through trade;
5. Reversal of capital flows;
6. Tightening of global financial conditions;
7. Slowing global growth.

The trigger could be disappointment from excessive capital expenditures, reassessment of profitability, and reassessment of the miraculous effect of AI implementation in the economy (I analyzed these processes in great detail in 2024-2025 long before the IMF narratives emerged).

▪️It is assumed that AI and technology are one of the few factors keeping US growth afloat amid slowing immigration and domestic consumption.

The IMF admits that under certain circumstances, AI could theoretically not only compensate for war (energy shock) and other macro imbalances but also lift the global economy to a higher trajectory.

Everything is rather at the hypothesis level. No one knows what real impact AI will have on the economy, employment, productivity, and technological progress.