Global Macro Research: AI governance

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27 February 2026 Fixed income

“For investors, appreciating the scale and complexity of the AI ecosystem is critical since entities can be exposed to different layers which carry different types of financial risks and their associated dependencies.”

Artificial intelligence (AI) is reshaping global economic, financial, and social systems with a speed and magnitude unseen in previous technological cycles. AI technologies can learn from data and solve problems in ways that resemble human thinking. AI is a layered, interdependent ecosystem involving physical, digital, and socio-economic components, where failures in one layer can cascade and amplify risks across the entire systems. This makes the risks associated with AI novel, complex and potentially fundamental.
For investors, this transformation is happening at pace and could introduce financially material risks to portfolios. As a non-linear, probabilistic, and self-amplifying system, AI can create unprecedented productivity opportunities and entirely new categories of operational, ethical, legal, reputational, social, and systemic risks. Perspectives from academics and hyperscaler incumbents highlight the adolescence of AI1 and financial materiality of its risks, underscoring the need for controls, model behaviour transparency and technical advances like interpretability and constitutional AI.
Sectors particularly vulnerable to AI risks include information technology, financials, healthcare, and retail, in our view.
AI governance will play a central role in how entities manage and respond to AI risks. It will function as an economic variable rather than an externality, and can directly influence company valuation. In our view, leadership in the use of AI requires careful review and design of enterprise arrangements, infrastructure systems, data provenance, model validation and integration in overall risk management, to survive and thrive in the AI-led transition. For these to interact effectively and efficiently, while mitigating risks, clear governance is essential.
Effectively assessing an entity’s approach to AI governance should focus on four dimensions: exposure, readiness, commercial strategy and execution, and monitoring and assurance. Insight sets out an initial approach to assessing a company’s AI governance based on these four dimensions – acknowledging that the pace of development in such a fast-moving space, such a framework will need ongoing review.
For capital allocators, there is a need to understand all of these components to effectively analyse and pick the winners and losers in this changing world.