This article examines how the convergence of artificial intelligence and geopolitical fragmentation is creating a new generation of interconnected risks. Traditional governance frameworks were designed for slower-moving and more predictable threats, but A
For decades, banks have managed emerging risks by
extending existing frameworks. New regulations led to new controls. New
technologies led to new governance processes. New market shocks led to revised
stress tests.
Today, that approach is being seriously tested on a
daily basis. The convergence of geopolitical fragmentation and artificial intelligence
is creating risks that evolve faster than many institutions can identify,
escalate, and manage them.
More importantly, these forces are increasingly
interacting with one another, creating a level of complexity that traditional
governance structures were simply not designed to handle.
The greatest challenge facing risk leaders, then, is
not simply geopolitical risk. Nor is it AI risk. It is the combination of the
two.
The Bank for International Settlements (BIS) has
warned that AI is increasing the complexity of the financial system itself. In
a January 2026 speech on financial stability, the BIS noted that AI can make
risks “more difficult to observe and assess” because of opaque models,
unstructured data, and growing reliance on third-party providers.
Diverging sanctions regimes, technology
restrictions, data localization requirements, and competing regulatory
standards are creating a world in which global consistency is becoming
increasingly difficult to achieve.
Recent analysis suggests that more than 70 countries
are developing distinct AI-related regulatory frameworks, and in the process
creating a patchwork of requirements that institutions must navigate simultaneously.
Artificial intelligence is accelerating these
pressures. “Artificial intelligence is
transforming financial services faster than existing
governance frameworks are evolving,” said Sonia Baxendale, President and CEO of
the Global Risk Institute.
She added that managing AI risk “is no longer
confined to individual institutions”
and increasingly requires coordination across the
wider financial ecosystem. Historically, risk management operated on relatively
predictable timelines.
A threat emerged, specialists analyzed it,
governance committees reviewed it, and
management approved a response. Today, AI-enabled systems
can generate decisions, identify vulnerabilities, or influence markets in near
real time.
The International Monetary Fund recently warned that
advanced AI models are dramatically reducing the time and cost required to discover
and exploit vulnerabilities in critical systems.
According to the IMF, AI-driven cyber attacks could
create “correlated failures” across multiple institutions because many banks
rely on common software, cloud providers, and technology platforms.
