BE Magazine - August 2026

The AI Question hanced. Supervisory coordination improved. More importantly, regula- tors shifted their mindset from over- seeing individual institutions in isolation to assessing interconnected systemic risk. One of the most consequential out- comes of these reforms was the recognition that certain institutions had become “too interconnected to fail.” Rather than waiting for collapse and improvising emergency rescues, regulators introduced mechanisms designed to ensure that systemically important institutions could with- stand severe shocks—or fail in a con- trolled manner without destabilizing the broader system. This regulatory maturity has impor- tant implications for AI. While the technology itself differs significantly from financial instru- ments, the governance logic devel- oped after 2008 offers a useful framework for assessing emerging vulnerabilities associated with con- centrated AI infrastructure and de- pendencies. A CONCENTRATED AI ECOSYSTEM The parallels between today’s AI sec- tor and pre-2008 finance are difficult to ignore. Much like the banking system before the global crisis, the AI ecosystem ex- hibits significant concentration. A limited number of companies domi- nate advanced large-language-model capabilities, cloud infrastructure, and semiconductor production. In enterprise-grade generative AI, a small cluster of technology firms cur- rently controls the overwhelming majority of market activity. Equally significant is the concentration at the hardware level, where advanced semiconductor manufacturing is heavily dependent on a narrow set of suppliers. This concentration introduces a new form of systemic exposure. If major AI providers become deeply embedded in financial institutions’ risk management, fraud monitoring, customer services, compliance systems, treasury operations, or in- vestment analysis, operational de- pendence on a small number of technology providers may become increasingly difficult to ignore. The concern is not merely commer- cial concentration. It is infrastructural concentration. A single disruption—whether tech- nological, geopolitical, regulatory, or environmental—could have cascad- ing operational implications across multiple jurisdictions and financial systems simultaneously. The temporary disruption to semi- conductor production in Taiwan fol- lowing the April 2024 earthquake served as a reminder of how geo- graphically concentrated parts of the global technology supply chain have become. In an era where financial institutions increasingly rely on com- puting power and AI-enabled sys- tems, resilience of underlying infrastructure deserves greater strate- gic attention. For Arab central banks and financial regulators, the issue is particularly relevant given the region’s acceler- ated investments in digital banking, fintech ecosystems, and cloud-based financial infrastructure. WHY THE FINANCIAL RISKS MAY BE CONTAINED Despite these concerns, there are strong reasons to believe that AI-re- lated financial risks can remain man- ageable—provided regulators act proactively and institutions strengthen operational preparedness. Unlike 2008, regulators are not ap- proaching this challenge without precedent or institutional memory. Global supervisory bodies already possess tools for identifying critical dependencies, assessing concentra- tion risk, and developing resilience requirements. What may be required is adaptation rather than reinvention. Several priorities deserve particular attention. FIRST: IDENTIFYING SYSTEMICALLY IMPORTANT AI INFRASTRUCTURE Financial supervisors may increas- ingly need to identify which technol- ogy providers have become essential to financial stability. This extends beyond AI developers themselves to include cloud-service providers, chip manufacturers, and digital infrastructure operators whose failure could disrupt critical financial services. The challenge today lies partly in vis- ibility. Regulatory frameworks for monitoring AI-related dependencies remain at an early stage, and mean- ingful data gaps persist. Without standardized reporting or common classifications, authorities may strug- gle to understand where concen- trated exposures truly exist. For financial institutions in the Arab region, this suggests a growing need for internal mapping of technology dependencies, particularly where critical functions rely heavily on ex- ternal AI systems. Boards and senior management should increasingly ask a straightfor- ward but strategic question: What happens if our primary AI provider becomes unavailable? OPERATIONAL RESILIENCE MUST BECOME A STRATEGIC PRIORITY The second imperative concerns re- silience. In traditional banking supervision, capital buffers help absorb losses during crises. AI systems, however, do not operate like balance sheets. Their vulnerabilities lie in opera- tional continuity, model availability, data access, and infrastructure relia- bility. the BANKING EXECUTIVE 34 ISSUE 212 AUGUST 2026