AI exposure Business and financial operations
Will AI replace financial specialists?
Financial Specialists, All Other. US occupation 13-2099.
The reading
22.0%
of the time financial specialists spend on their work goes on tasks where AI is already being used to do that work.of financial specialists' working hours go on tasks AI has already started taking off their plate.
Ranked 107 of 756 US occupations. More exposed than 85% of them.Further along than 85% of them.
Per cent of working time Square-law scale
Average US job 7.7%
Well above the typical job.Ahead of most of the workforce.
What AI already does for financial specialistsWhat financial specialists no longer do alone
O*NET lists 44 tasks for financial specialists. AI use at work shows up in 9 of them. Each score runs from 0.5, where every observed use helps a person with the task, to 1, where every use does the task outright.
- Design, implement, or maintain fraud detection tools or procedures.Core task mostly automated 1.00
- Identify, track, or maintain metrics for trading system operations. mostly automated 1.00
- Produce written summary reports of financial research results.Core task mostly automated 0.95
- Interpret results of financial analysis procedures.Core task mostly automated 0.91
- Apply mathematical or statistical techniques to address practical issues in finance, such as derivative valuation, securities trading, risk management, or financial market regulation.Core task mostly automated 0.90
- Provide application or analytical support to researchers or traders on issues such as valuations or data.Core task mostly automated 0.88
- Research or develop analytical tools to address issues such as portfolio construction or optimization, performance measurement, attribution, profit and loss measurement, or pricing models.Core task mostly automated 0.86
- Prepare requirements documentation for use by software developers. automated and assisted 0.82
Show the other 1
- Prepare written reports of investigation findings.Core task automated and assisted 0.73
What it does not touch, yetWhat still needs a human
35 of the 44 tasks show no AI use at work in the data.
- Advise businesses or agencies on ways to improve fraud detection.Core task
- Analyze financial data to detect irregularities in areas such as billing trends, financial relationships, and regulatory compliance procedures.Core task
- Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope.Core task
- Conduct field surveillance to gather case-related information.Core task
- Conduct in-depth investigations of suspicious financial activity, such as suspected money-laundering efforts.Core task
- Confer with other financial engineers or analysts on trading strategies, market dynamics, or trading system performance to inform development of quantitative techniques.Core task
Show the other 29
- Consult traders or other financial industry personnel to determine the need for new or improved analytical applications.Core task
- Coordinate investigative efforts with law enforcement officers and attorneys.Core task
- Create and maintain logs, records, or databases of information about fraudulent activity.Core task
- Define or recommend model specifications or data collection methods.Core task
- Develop core analytical capabilities or model libraries, using advanced statistical, quantitative, or econometric techniques.Core task
- Devise or apply independent models or tools to help verify results of analytical systems.Core task
- Document all investigative activities.Core task
- Evaluate business operations to identify risk areas for fraud.Core task
- Gather financial documents related to investigations.Core task
- Interview witnesses or suspects and take statements.Core task
- Lead, or participate in, fraud investigation teams.Core task
- Maintain knowledge of current events and trends in such areas as money laundering and criminal tools and techniques.Core task
- Maintain or modify all financial analytic models in use.Core task
- Prepare evidence for presentation in court.Core task
- Recommend actions in fraud cases.Core task
- Research new financial products or analytics to determine their usefulness.Core task
- Research or evaluate new technologies for use in fraud detection systems.Core task
- Review reports of suspected fraud to determine need for further investigation.Core task
- Testify in court regarding investigation findings.Core task
- Train others in fraud detection and prevention techniques.Core task
- Analyze pricing or risks of carbon trading products.
- Arrest individuals to be charged with fraud.
- Assess the potential impact of climate change on business financial issues, such as damage repairs, insurance costs, or potential disruptions of daily activities.
- Collaborate with product development teams to research, model, validate, or implement quantitative structured solutions for new or expanded markets.
- Develop methods of assessing or measuring corporate performance in terms of environmental, social, and governance (ESG) issues.
- Develop solutions to help clients hedge carbon exposure or risk.
- Develop tools to assess green technologies or green financial products, such as green hedge funds or social responsibility investment funds.
- Negotiate with responsible parties to arrange for recovery of losses due to fraud.
- Obtain and serve subpoenas.
How that compares
Among the 29 business and financial operations occupations, financial specialists rank 10. The group averages 17.7%, and its most exposed job is Market Research Analysts and Marketing Specialists at 64.8%. The average US occupation sits at 7.7%.
Just above in the ranking
- 104Geological Technicians, Except Hydrologic Technicians 22.9%
- 105Dispatchers, Except Police, Fire, and Ambulance 22.6%
- 106Film and Video Editors 22.3%
Just below
What this does and does not mean
Exposure is observed use, not a forecast. Anthropic maps work conversations with Claude onto the tasks O*NET lists for each job and asks, of the tasks AI could speed up, which are actually being used for at work. A use that does the task outright counts in full and a use that assists a person counts half. The task scores are averaged into the occupation figure by the share of time spent on each task.
A high figure means AI is already part of how this work gets done. It does not mean anyone has been replaced. Anthropic's own reading of the labour market finds no systematic rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting exposed jobs.No measurable rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting these jobs. Gap years for everyone. Labor market impacts, 5 March 2026.
Task list and titles from O*NET 31.0 by the US Department of Labor, Employment and Training Administration, used under the CC BY 4.0 licence. Scores from the Anthropic Economic Index (CC BY). Checked 1 November 2026. How the ranking works.