Macro Markets and Machines_The Economic and Market Transformation Driven by AI_GWM report - Flipbook - Page 34
Macro, Markets, and Machines
November 2025
Regarding China, which sees high- and low-TFP 10-year gains of 3.5 p.p. and 1.2 p.p., respectively, the study
notes that while China has strong preparedness in innovation and infrastructural preparedness, its higher
manufacturing share of the economy (28% versus the United States’ 16%) and lower share of AI-intensive
employment in other sectors limit AI gains.
Exhibit 26 – Potential GDP Gains May Be Uneven
GDP increase versus baseline
10 years ahead
6%
5%
4%
3%
2%
1%
0%
ROW
LIC
EMA
EML
CHI
Low TFP
High TFP
EUS
OAD
USA
World
Notes: CHI = China. EMA = Emerging Market Economies Asia, Central Asia, Russia, etc. EML = Emerging Market Economies Latin America, Middle
East, Africa, etc., EUS = EU and Switzerland. LIC = Low-Income Countries. OAD = Other Advanced Economies.
Sources: IMF; Scotia Wealth Management.
Section 4.6: Within-Economy AI Benefits Vary Across Industries
Beneath aggregate macroeconomic impacts and cross-country performances, the IMF simulates how
different sectors in the economy benefit from AI adoption. In its study, the IMF disaggregates economies into
three main sectors: tradable, non-tradable, and AI-intensive industries. As previously mentioned, the shares that
these industries represent in a country’s economy can have important implications for economy-wide AI gains,
as each of these sectors exhibit varying degrees of AI tailwinds. Differences in within-country and within-sector
AI preparedness and exposures also mean that one country’s AI-intensive sector could derive smaller AI gains
than the same sector in another country.
Unsurprisingly, the AI productivity boost to AI-intensive industries is greater than in non-tradable and
tradable sectors across the regions that the IMF focuses on. The gap between the benefits accrued by each
industry is roughly proportional for most countries and regions (Exhibit 20 again). In the United States, under
a high-TFP scenario, AI-intensive sectors see about a 5–5.5 p.p. productivity boost compared with about a
2.5–3.0 p.p. gain for the tradable sector, or roughly half, with the non-tradable sector sitting about halfway
between the two extremes at a touch above 4 p.p.
In the United States, AI-intensive industries have an AI exposure value of 0.85, with this figure representing
the proportion of employment in each sector that is considered highly exposed to AI (i.e., 85%). In comparison,
the non-tradable and tradable sectors have respective AI exposure shares of 67% and 43%, respectively.
Exhibit 27 lists a summary of the industries that fall into each of the three AI-intensive, tradable, and nontradable sectors, with the likes of finance and insurance and telecommunications and information technology
among those in the AI-intensive sectors where 85% of jobs would be highly exposed to AI.
Scotia Wealth Management
33
