- Big banks are growing AI hiring even as overall headcount stays flat or falls, shifting work away from non-front-office roles.
- In Europe, AI and digitalisation could cut ~200,000 banking jobs (~10%) by 2030, hitting back/middle office, compliance, and risk hardest.
- Applicant volumes are surging while hiring is ultra-selective, with Goldman and Bank of America taking under 1% of huge pools.
- Banks are replacing fewer leavers and using AI to automate tasks, prioritising client-facing and revenue-generating hires.
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The banking sector is at an inflection point where the rising promise of AI meets the reality of hiring constraints. Across major institutions, there’s a consistent pattern: investment in AI roles is accelerating even as total headcount management has grown tight. This reflects a strategic imperative—leveraging automation and intelligent systems to absorb non-front office tasks, while preserving or expanding roles tied directly to revenue and client-facing activities.
For Europe, the Morgan Stanley forecast signals substantial structural risk: a marked reduction in support, compliance, and operations roles could weigh heavily on career trajectories and labor dynamics therein. That transition raises questions about how remaining roles will be valued and taxed, how institutions will maintain controls and regulatory compliance with leaner teams, and whether remote hubs or offshoring might offset some of the job loss.
At elite U.S. banks like Goldman and Bank of America, outsize applicant pools and ultra-low acceptance rates reinforce that hiring remains a privilege sharply reserved for a tiny fraction. These dynamics may accentuate concerns over diversity, burnout, and access—especially given that many junior and non-client facing roles are being hollowed out or redesignated. Even when grad intake remains robust, maintenance hiring and replacement cycles are slow: jobs vacated are often left undone or absorbed elsewhere, contributing to ever-leaner staffs.
Strategically, banks that get AI adoption right may benefit from sharply improved cost-income ratios, more scalable growth, and competitive resilience. But there’s a risk: if AI becomes a blunt tool that displaces human judgment prematurely—especially in critical or regulatory functions—banks may face risks to culture, oversight, and institutional knowledge.
Open questions include: What governance frameworks will ensure AI augmentation doesn’t erode essential skills? How will banks balance efficiency gains with talent pipelines for front-line and client facing work? And how is compensation being impacted across roles as AI changes productivity perceptions?
Supporting Notes
- Banks tracked by Evident increased AI-related talent by ~13% over six months; AI roles rose from just over 60,000 in September 2023 to nearly 80,000 by March 2025, while total bank headcounts declined ~3% over the past two years.
- Morgan Stanley estimates that more than 200,000 jobs—~10% of staff across 35 major European banks (of 2.12 million employees)—could be cut by 2030 due to AI and digitalisation, particularly in central services (back and middle office, compliance, risk).
- Goldman Sachs received about 875,000 applications for experienced roles and another ~300,000 for internships; both cohorts saw acceptance rates below 1%.
- Bank of America hired 2,000 Gen Z graduates from a pool of 200,000 applicants even as it holds overall headcount essentially flat, thanks to attrition being only ~7.5%—roughly half the level seen in 2016 (~16%)—and a practice of not immediately replacing many departing staff [initial article; 3].
- BofA and other banks report that AI has replaced ~30% of coding tasks; Moynihan claimed savings of roughly 2,000 jobs via coding automation and generative AI tools [initial article; 2].
- Citi has built an internal AI workforce of ~4,000 people via its AI Champions and Accelerators program, with some roles serving to spread adoption rather than to develop core models.