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AI is likely to shrink or reshape some entry-level work at large financial institutions, but current evidence does not show that it will eliminate junior banking jobs across the board. The near-term change is more likely to come through automation of routine tasks, fewer vacancies or hires in some teams, and higher output expectations for the people who remain. For new graduates, the practical question is not whether finance will stop hiring, but which tasks are changing and what human judgment, control and client skills will still be needed.
What the evidence says about entry-level job cuts
The strongest recent workforce figure is cross-industry, not bank-specific. A Morgan Stanley survey published February 5, 2026, of 935 executives in the United States, Germany, Japan and Australia found average productivity growth of 11.5% and a net headcount decline of 4% across five sectors it judged highly exposed to AI. Respondents said AI eliminated 11% of jobs and left another 12% unfilled, partly offset by 18% new hires. Morgan Stanley reported that cuts were more pronounced at larger corporations and mostly affected entry-level employees.
Those figures describe survey respondents across several exposed sectors; they are not a forecast that banks, or any named bank, will cut 4% of staff. They do support a more limited conclusion: when companies use AI to raise productivity, junior work and hiring pipelines can be affected early. A firm might automate part of an analyst’s workload, hire fewer people into a team, or leave an open role vacant rather than remove an entire job category.
What large banks have disclosed
Goldman Sachs’ 2024 annual report describes a three-year program to optimize its organizational footprint and increase automation and productivity through AI. It says the firm provided many employees with a developer copilot and a natural-language GS AI assistant, with these tools being expanded into day-to-day workflows during 2025. That is evidence of deployment and intended efficiency gains, not a disclosed count of analyst positions eliminated.
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JPMorgan Chase CEO Jamie Dimon’s 2025 shareholder letter warns: “There is a possibility that AI deployment will move faster than workforce adaptation to new job creation.” That is a risk assessment, not a published forecast of how many JPMorgan jobs will go. The company’s August 13, 2024 workforce article also describes apprenticeships in technology, business operations and finance, alongside a $350 million global workforce investment.
Which finance work is most exposed?
Exposure depends less on a job title than on the work inside it. J.P. Morgan Asset Management’s generative-AI report says AI seems unlikely to automate many entire jobs, while having significant potential to automate tasks within them. It estimates that most aggregate task-exposure estimates fall between 20% and 30%, and says AI will augment rather than entirely replace human capabilities in the vast majority of cases. These are broad task estimates, not a prediction for a particular bank role.
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| Work area | Tasks more exposed to automation | Human work that remains important |
|---|---|---|
| Investment banking and corporate finance | Routine research, document preparation, data handling, first-pass review and standardized reporting. | Checking assumptions, interpreting a client’s circumstances, negotiating, exercising judgment and taking responsibility for advice or work product. |
| Operations and control functions | Repetitive, rules-based processing, document review and standardized customer-service workflows. | Escalating exceptions, investigating unusual cases, applying policy to context and ensuring required controls are followed. |
| Technology and analytics | Some routine coding assistance, data handling and repeatable analysis. | Defining the problem, validating outputs, understanding systems and data, and making decisions about how work should be implemented. |
| Financial advice and client service | Standardized information and portfolio tasks that can be handled through digital tools. | Complex financial decisions, emotional intelligence, client context, crisis conversations and accountability. |
The table describes relative task exposure, not a ranking of occupations or a guarantee that any listed task will be automated at a particular employer. J.P. Morgan Asset Management’s financial-advice example makes the distinction especially clear: robo-advisers can provide customized investment advice and portfolio management, while human advisers remain important for complex matters, judgment, emotional intelligence and crisis context.
Why junior roles may change before whole occupations disappear
Entry-level positions often include a concentrated share of work that is repetitive, document-heavy or standardized. If software makes that work faster, a team may need fewer junior hours for the same output. That can affect recruitment without producing a headline announcement that an occupation has been replaced: a bank may reduce analyst-class hiring, leave vacancies unfilled, or expect each junior employee to produce more.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Large institutions may be able to deploy tools across many workflows, and Morgan Stanley’s survey found the largest respondent companies had the highest net position cuts. Goldman Sachs’ firm-wide AI tools and organizational-footprint program show how a major institution can pursue productivity changes at scale. Neither point establishes how many jobs any specific bank will remove; outcomes depend on adoption, regulation, controls, economic conditions and management decisions.
Is AI going to replace entry-level investment banking analysts?
There is no established bank-wide percentage showing how many investment banking analyst positions AI will replace. Analysts may spend less time on routine research, document preparation, first-pass review and standardized reporting as tools take on parts of those tasks. But an analyst role also involves checking information, understanding a transaction’s context, coordinating with colleagues and responding to changing client needs. Those responsibilities do not disappear simply because a tool can draft or summarize material.
The more defensible expectation is uneven change: particular teams may need fewer junior hours or hire fewer analysts, while other teams continue hiring and use AI to increase the volume or speed of work. The Morgan Stanley survey is relevant as a cross-industry signal, but it cannot be used as a specific investment-banking headcount forecast.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to assess risk at a particular bank or role
A job title alone will not tell a candidate how exposed a role is. Look at the actual workflow and the institution’s staffing choices:
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- Routine, document-based work: A role made up largely of repeatable data handling, first-pass review or standardized reports has more tasks that software may assist with.
- Accountability and regulation: Work requiring judgment, fiduciary or regulatory responsibility, client context, or an accountable sign-off still needs appropriate human oversight.
- Internal tools and data: Consider whether the firm has reliable proprietary data and internal AI systems that can be used within its controls; having a tool does not itself show that a job will be eliminated.
- Hiring behavior: Distinguish announced layoffs from smaller incoming classes, unfilled vacancies and redeployment. These are different ways staffing can change.
- Training access: Ask whether the employer offers apprenticeships, technical training or a route to move into work that combines finance knowledge with technology and control responsibilities.
What should a new finance graduate learn?
Build skills that help you use automated output responsibly and handle the parts of finance that require context. Tool familiarity can be useful, but it is not a substitute for knowing whether an answer is accurate, relevant and appropriate to use.
- Financial fundamentals: Learn accounting, valuation, markets and how to explain the assumptions behind an analysis.
- Data and technology literacy: Become comfortable working with structured data, spreadsheets and coding or AI tools relevant to your chosen role. Validate outputs rather than treating generated material as authoritative.
- Review and control: Practice tracing a conclusion to its underlying information, spotting inconsistencies and documenting decisions clearly.
- Communication and judgment: Develop the ability to explain findings, ask precise questions, work with colleagues and recognize when a situation needs escalation or a human decision.
- Adaptability through training: Seek employers that make learning and internal mobility concrete. JPMorgan’s described apprenticeships in technology, business operations and finance are one example of a structured workforce pathway, not a guarantee of employment.
Dimon’s 2025 warning is also a reminder that reskilling is not solely an individual responsibility. He calls for responses including retraining, income assistance, reskilling, early retirement and relocation support for workers adversely affected by AI. JPMorgan’s workforce article likewise describes apprenticeships and investment in workforce programs. These measures address the possibility that some workers will need help moving into new roles; they do not prove that every displaced worker will transition smoothly.
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