Macro Markets and Machines_The Economic and Market Transformation Driven by AI_GWM report - Flipbook - Page 13
Macro, Markets, and Machines
November 2025
All else equal, AI’s role as a capital-deepening technology may create a structural tailwind for equities
relative to other asset classes as the capex cycle raises the capital share at the expense of the labour share.
Companies that successfully integrate AI into workflows may be able to position themselves to expand margins
by lowering costs, augmenting certain work through AI, while reducing headcount across certain functions. That
said, equity market leadership will be influenced by phases of adoption. In the current build-out phase, we are
seeing the primary beneficiaries being the suppliers of AI infrastructure. This includes semiconductor companies
like Nvidia Corporation that are capitalizing on robust demand for GPUs and other specialized chips. U.S.
hyperscalers such as Amazon.com, Inc., Microsoft Corporation, Alphabet, and Meta Platforms, Inc. dominate the
cloud infrastructure that underpins AI model training and deployment. Utilities may be positioned to benefit
from rising electricity demand, while industrial firms and firms tied to data centre construction capture the
physical side of this build-out phase. As adoption matures, winners will likely broaden with profitability
improving across a wide array of industries.
Corporate profit margins in advanced economies, particularly in the United States, have been strong in the postpandemic era, supported by unprecedented policy stimulus, robust consumer demand, and firms’ ability to pass
through higher input costs. However, margins have since receded somewhat. While still resilient by historical
standards, they are no longer at their peak, reflecting an increasingly challenging cost environment. Global supply
chains remain fragile, with firms still exposed to bottlenecks in semiconductors, energy, and critical inputs. Tariffs
and the broader shift toward protectionism have raised import costs and re-shaped outsourcing strategies. The
push toward nearshoring and reshoring, while improving resilience after the post-pandemic supply shortage,
entails higher operating costs compared with offshore production. On top of this, the environmental transition is
another factor, with decarbonization targets requiring capital-intensive upgrades to equipment and pre-existing
energy systems. Meanwhile, labour costs continue to rise as ageing demographics tighten labour supply and
union activity remains strong (more so in Canada and Europe than in the United States).
Left unchecked, these factors suggest that margins could face persistent headwinds in the years ahead. This
is exactly where AI can act as an offset. If the technology can successfully lower the cost of key business
functions, improve efficiency, and raise output, it would provide businesses a way to counter these cost
pressures. For instance, healthcare companies may increasingly come to rely on AI systems for billing, insurance
processing, and administrative processes. This could be a game-changer, as administrative costs account for
15%-25% of total national healthcare expenditures in the United States (Chernew, Mintz, 2021). Another
example is in the consumer goods sector, as smarter logistics can help make supply chains more resilient, while
tightly regulated sectors, like finance, can leverage AI to automate and improve compliance, reporting, and
document review functions.
Scotia Wealth Management
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