Macro Markets and Machines_The Economic and Market Transformation Driven by AI_GWM report - Flipbook - Page 31
Macro, Markets, and Machines
November 2025
Exhibit 22 – Higher Share of AI-Intensive and Non-Tradable Sectors Influences AI Benefits
100%
90%
80%
% of GDP
70%
60%
50%
40%
30%
20%
10%
0%
CHI
EMA
EML
AI-intensive
EUS
LIC
Non-tradable
AE
US
ROW
Tradable
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.
Beyond the sectoral-split exposure to AI, within-sector exposures are also important to determining the
benefits of AI for each country. Across tradables, non-tradables, and AI-intensive industries, workers enjoy
different degrees of technological integration in their day-to-day tasks due to the requirements of their roles or
the availability and sophistication of technological resources. In turn, the adoption of AI would have a bigger or
smaller influence on worker productivity for a representative employee in industry A in country X compared with
one also in industry A but in country Y.
To estimate how AI may affect each country’s workers differently and calibrate its aggregate economic
impact, the IMF considers the share of employment that is deemed highly exposed to AI and thus more likely
to see a larger and faster impact on productivity. The authors analyze the overlap between the different tasks
that make up a given role and the capabilities of AI and determine that 85% of U.S. workers in AI-intensive
industries are highly exposed to AI, slightly above the 82% share for the European Union but well above China’s
58%. Combined, the United States’ 16.3% GDP share of AI-intensive industries, with 85% of its workers being
highly exposed to AI, places it at a much stronger starting point to reap AI benefits than China with a 12.1%
AI-intensive economy share, with only 58% of its workers highly exposed to AI.
2.
Preparedness
Countries that are better prepared at the outset of a new technology are in a position to more fully harness
its potential. As discussed earlier in this report, even if an economy has a high exposure score, its ability to
integrate AI effectively depends on preparedness.
The IMF’s AI Preparedness Index (AIPI) evaluates countries’ AI readiness based on four factors (Exhibit 23):
digital infrastructure, innovation and economic integration, human capital and labour market policies, and
regulation and ethics.
A.
Digital infrastructure refers to the strength of technological resources and availability, as a foundation
for a faster diffusion and application of AI.
B.
Innovation and economic integration represent the country’s technological development momentum
via research and development spending, credit availability, or its openness to international trade
markets and foreign investment (and expertise).
Scotia Wealth Management
30
