# Will AI replace risk managers? Updated October 2026 Financial risk specialists score 60 of 100 for AI exposure. The largest share of their task time, 80%, is work AI speeds up while they stay in charge. AI can take over the other 20% outright. - **20%** AI can do it - **80%** AI helps High exposure Higher than 91% of the 923 occupations we scored. ## Task by task We graded 30 tasks, listed here from most to least exposed. AI can do 6 of them today, speeds up 24 and leaves 0 to people. | Task | AI exposure | | --- | --- | | Draw charts and graphs, using computer spreadsheets, to illustrate technical reports. Spreadsheet assistants generate charts from data readily. | 75% AI can do it | | Track, measure, or report on aspects of market risk for traded issues. Risk measurement is largely systematic; AI handles routine reporting. | 68% AI can do it | | Document, and ensure communication of, key risks. Drafting risk documentation is strong AI work; distribution needs oversight. | 65% AI helps | | Gather risk-related data from internal or external resources. Pulling data from databases and filings is largely automatable. | 65% AI can do it | | Maintain input or data quality of risk management systems. Data validation rules are automatable; oversight stays human. | 65% AI can do it | [See what AI can take on across a finance team](https://www.aigentcy.com/ai-for/finance/) ## How financial risk specialists compare All occupations (923) Business and financial operations (48) **Financial risk specialists score 60**, marked by the dark line. Each dot is a score, darker where more occupations share it. The short marks show the averages, 37 for all occupations and 55 for business and financial operations. ## Pay and outlook in the US Median pay $117,330 a year, May 2025 People employed 63,850 in the US, May 2025 Projected change in jobs +7.4% from 2024 to 2034 ## Skills to build - Run value-at-risk and stress models in Python or R - Write SQL queries that pull position and exposure data - Build risk dashboards for committees in Power BI or Tableau - Maintain data quality rules in risk management systems - Hold the FRM credential from GARP ## Safer roles nearby 5 related occupations with lower scores. - [Financial quantitative analysts58 out of 100](https://www.aigentcy.com/ai-exposure/financial-quantitative-analysts/) - [Financial analysts58 out of 100](https://www.aigentcy.com/ai-exposure/financial-analysts/) - [Investment fund managers53 out of 100](https://www.aigentcy.com/ai-exposure/investment-fund-managers/) - [Management consultants55 out of 100](https://www.aigentcy.com/ai-exposure/management-consultants/) - [Financial examiners49 out of 100](https://www.aigentcy.com/ai-exposure/financial-examiners/) ## Questions about financial risk specialists and AI Will risk managers be replaced by AI? Partly. About 5 in 10 working hours go to tasks AI can already do, mostly drawing charts in spreadsheets and routine market risk reporting. Live conversations with traders, clients and committees stay with people. Which tasks will AI take from financial risk specialists? Chart drawing in Excel goes first, with an exposure score of 75, since spreadsheet assistants build charts from data readily. Market risk tracking follows at 68, because measuring risk for traded issues is largely systematic. Gathering risk data from databases and filings sits at 65, since those pulls are largely automatable. Which tasks stay with financial risk specialists? Trader conversations stay human, since they are live and AI only prepares briefing notes. Client meetings on value-at-risk and market scenarios stay human for the same reason. Investment recommendations stay with people because they carry a legal duty that an accountable adviser must own. How can financial risk specialists stay valuable? Take responsibility for the data and model checks behind every risk number. Validate inputs in SQL and Python before any report reaches a committee, and log each rule you change. Test value-at-risk outputs in R or Python, then walk traders and clients through the results in person. Keep the FRM credential current, since employers still expect a named professional behind each figure. ## Related jobs - [Financial advisors60 out of 100](https://www.aigentcy.com/ai-exposure/financial-advisors/) - [Stockbrokers64 out of 100](https://www.aigentcy.com/ai-exposure/stockbrokers/) - [Credit analysts62 out of 100](https://www.aigentcy.com/ai-exposure/credit-analysts/) - [Financial managers49 out of 100](https://www.aigentcy.com/ai-exposure/financial-managers/) ## Next steps for financial risk specialists - ### Check your job Your job title is a rough guide. Your actual tasks decide your score. Paste your job description or CV and see which of your tasks AI can do. [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/) ### Check which roles in your team AI can take on We map your team's tasks, show what AI can do today and build the automations that pay back first. [Book an AI audit](https://www.aigentcy.com/audit/) ## Related topics - [**Jobs AI can't replace**Cement masons score lowest, at 8.](https://www.aigentcy.com/ai-exposure/jobs-ai-cant-replace/) - [**Jobs most at risk from AI**Proofreaders score highest, at 76.](https://www.aigentcy.com/ai-exposure/jobs-most-exposed-to-ai/) - [**High-paying jobs with low AI exposure**Radiologists earn a median $420,860 and score 46.](https://www.aigentcy.com/ai-exposure/high-paying-jobs-low-ai-exposure/) - [**Entry-level jobs with low AI exposure**Cement masons need little prior training and score 8.](https://www.aigentcy.com/ai-exposure/entry-level-jobs-low-ai-exposure/) - [**Jobs AI speeds up the most**For natural sciences managers, AI speeds up 96% of task time.](https://www.aigentcy.com/ai-exposure/jobs-ai-speeds-up/) - [**AI and jobs in Malta**15 iGaming roles graded task by task.](https://www.aigentcy.com/ai-exposure/malta/) - [**Skills that keep work human**The skills to build in the jobs AI changes least.](https://www.aigentcy.com/ai-exposure/skills/) - [**Jobs A to Z**Every job we publish, by first letter.](https://www.aigentcy.com/ai-exposure/jobs/) - [**AI exposure by industry**Average scores for 22 occupation groups.](https://www.aigentcy.com/ai-exposure/industries/) - [**Write a CV screening software can read**How applicant tracking systems read a CV, and what to change.](https://www.aigentcy.com/ai-exposure/cv-screening-guide/) - [**AI for businesses**The tasks to automate first in each team and industry.](https://www.aigentcy.com/ai-for/) - [**How we score AI exposure**The grading, the weights and every source.](https://www.aigentcy.com/ai-exposure/methodology/) Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.