Macro Markets and Machines_The Economic and Market Transformation Driven by AI_GWM report - Flipbook - Page 49
Macro, Markets, and Machines
November 2025
Investment competition must not erode fiscal capacity. The race to attract AI activity risks a race to the
bottom, with tax holidays and one-off incentives proliferating even as digital tax rules remain unsettled.
The principle is disciplined competition: compete on fundamentals (skills, infrastructure, and regulatory
certainty) while cooperating on guardrails such as minimum tax standards, anti-avoidance rules, and coherent
treatment of intangibles. This approach supports capital formation while preserving the revenue base needed
to fund complements.
Scarce inputs and strategic locations are emerging as chokepoints. Access to reliable power, grid capacity,
cooling, chips, and critical minerals is increasingly shaping siting and pricing decisions, creating rents and
potential distortions. Policy should acknowledge scarcity without amplifying it: price inputs transparently, plan
infrastructure over multi-year horizons, and avoid bespoke deals that undermine contestability. Where public
interests, such as security, resilience, affordability, and climate sustainability, are at stake, governments should
pursue strategic, long-term coordination with trusted partners, replacing fragmented approaches that risk a
further destabilizing path ahead.
Resilience must evolve to match the complexity and scale of emerging risks. These go well beyond model
errors, encompassing cloud outages, synthetic media fraud, cyberattacks on data pipelines, and feedback loops
from models trained on AI-generated content. Financial markets add another layer of vulnerability, with
concentrated leadership in AI-linked equities and capex cycles tied to compute and energy increasing the risk of
correlated downturns. The priority is system-level assurance: stress-test dependencies, monitor concentration,
clarify accountability across third-party providers, and stress test systems – ensuring readiness without
slowing innovation.
Section 5.5: Steering from Tension to Transformation
Early days call for humble economics. Most macro claims about AI remain model based and hinge on adoption,
complements, and diffusion. That uncertainty demands a practical playbook, one that holds across a wide range
of AI futures. The goal is to act where evidence is strong, hedge where uncertainty is high, and coordinate where
spillovers are systemic.
This is not about reinventing the productivity policy wheel. Amid the AI hype, the foundations remain familiar:
better resource allocation, open and competitive markets, reliable infrastructure, and deep finance raise
productivity – with or without AI. As the IMF underscores, traditional structural reforms often deliver larger and
more certain productivity payoffs than speculative AI gains. AI can amplify, not replace, these foundations.
A credible AI playbook is necessarily all-encompassing. The impacts of AI will likely touch nearly every part of
society. Where gains are transformational, accelerate diffusion; where the path is transitional, cushion and
adjust; where tensions loom, mitigate risks without derailing innovation (see Box 1 on next page). The scope and
complexity of actions reinforce a core principle: productivity and welfare remain the central goals of economic
policy, and progress demands clear accountability.
Sometimes the smartest answer – even from AI – is “I don’t know.” It is not a failure of foresight; it is the
beginning of sound policy. In a world of complex, high-stakes decisions, embracing uncertainty with discipline
and direction is how real transformation takes root.
Scotia Wealth Management
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