We asked 1,178 people who work in financial services how they use AI at work. They answered The AI Report’s Where You Stand benchmark between July 20, 2026 and November 2, 2026. Here is how far along they are, what holds them back, what they want from AI next and which tools the most advanced teams use, compared with all 14,452 people in the benchmark.
Key findings
- People in financial services are close to the benchmark average. 16% are leaders, against 14% of all respondents, and 64% are still early.
- The biggest blocker is picking the right tools (32%), almost tied with the skills gap (32%).
- Their top goal is to save time (44%).
- ChatGPT is the most used AI tool (79% of those who named a tool), then Claude (69%) and Gemini (46%). Tableau stands out: 4% use it, against 2% of all respondents.
- Leaders lean on Claude. 77% of leaders use it, against 64% of those still early.
How far along people in financial services are with AI
The largest share of people in financial services say they are “just exploring” (36%). 9% say AI is used across their company and 7% are rolling it out to their team.
- Just exploring
- Testing a few tools
- Using 1 to 3 tools for real
- Rolling out to their team
- Used across the company
- Helping others with AI
What holds people in financial services back
We asked for the single biggest blocker. Picking the right tools leads at 32%. If that is you too: shortlist tools by the job you need done.
- Financial services
- All respondents
What they want from AI in the next 90 days
44% want to save time, 28% want to build their AI skills and 11% want to grow revenue.
- Financial services
- All respondents
The AI tools people in financial services use
People named 3.1 AI tools each on average. These are the 12 most used, as a share of the 1,069 people here who named at least one. Compare any of them in our AI tool database.
- Financial services
- All respondents
What the leaders use differently
Leaders are the 187 people in financial services whose AI is rolled out to their team or used across their company. They named 3.5 tools each, against 2.9 for the 749 who are still early. These are the clearest differences.
| Tool | Leaders | Early | Gap |
|---|---|---|---|
| Claude | 77% | 64% | +14 pts |
| Microsoft Copilot | 18% | 8% | +10 pts |
| Power BI | 18% | 11% | +7 pts |
| Tableau | 7% | 4% | +4 pts |
| Figma | 6% | 2% | +3 pts |
- Share of each group who use the tool. Leaders: 181 people, early: 656 people.
Where they use AI at work
Writing comes first (61%), then personal productivity (59%) and research (51%). People could pick several areas.
- Financial services
- All respondents
- Asked July 20 to August 31, 2026: 734 answers.
Budget for a first AI project
48% are not sure yet. The most common amount named is under $500 (27%).
- Financial services
- All respondents
- Asked from September 1, 2026: 446 answers.
Who answered
48% decide, recommend or have a say in what their company buys.
Company size
- Financial services
- All respondents
Role
- Financial services
- All respondents
Say in what their company buys
- Financial services
- All respondents
What leaders told The AI Report podcast
“Most average business users don't understand what they've just allowed there, which is suddenly that thing can access all of that data.”
Cillian Kieran, CEO and Founder at Ethyca. Think before you click accept on an AI connector. Linking an assistant to your CRM, Stripe, QuickBooks or Shopify can quietly give it access to everything in those systems. Cillian describes how, over ten or twelve weeks of casual questions, a small store owner could move sensitive purchase and card data across boundaries it shouldn't cross without realizing it. Understand exactly what you are permitting before you connect a system, and limit access to what the task actually needs. Watch or read the episode.
“We want our AI to know everything, not just one slice of the overall financial picture.”
Braden Warwick, Financial Planning Product Architect at PWL Capital. Connect your data before you buy more AI point tools. PWL Capital had already joined up its CRM, onboarding, planning and portfolio data in a data lake, so it is building its own meeting-notes tool designed to draw on each client's full picture, instead of adding one more vendor plugin that only knows a single slice. Watch or read the episode.
“You're not even actually looking for perfection. You're actually looking for improvement.”
Jason Li, CTO at Laurel. Before deciding what to automate, find out where time actually goes. Laurel captures real activity data rather than surveys, sorts it into the firm's own categories of work, and flags repeatable, low-judgment tasks like data entry and document assembly. Leaders can then decide whether the fix is a new hire or an AI tool, for example when senior partners are losing hours to internal admin instead of winning clients. Watch or read the episode.
Next steps
- Shortlist tools by the job you need done. The AI Report tool database compares 5,500+ AI tools by use case and price.
- Join the free live Claude session. Every Tuesday at 2pm ET, free for every reader.
- Get a plan built for you. The AI Report Pro turns your benchmark answers into a 90-day AI plan, step by step.
How do you compare?
Answer the same nine quick questions as these 14,452 people. See which of five AI types you are, how you compare with readers like you, and get a free 30-day AI roadmap by email.
Free. You also get The AI Report, the five-minute AI briefing, every weekday. Unsubscribe anytime.
Compare with other groups
The full benchmark: AI at Work Benchmark 2026, with every industry, role and company size side by side.
By industry: Professional services, Healthcare, Software and tech, Education, Marketing and media, Manufacturing, Nonprofits and government, Retail and e-commerce, Real estate, Legal.
By role: Executives and founders, Directors, Managers and team leads, Individual contributors, Consultants and advisors, Students and career switchers.
By company size: Solo professionals, Small businesses (2 to 50), Mid-size companies (51 to 1,000), Large enterprises (1,001+).
About this data
These numbers come from The AI Report’s Where You Stand benchmark. Between July 20, 2026 and November 2, 2026, 14,452 people completed it. This page covers the 1,178 who said they work in financial services.
- Answers are self-reported. People chose their own industry, role, company size and stage.
- “Early” means just exploring or testing a few tools. “Leaders” means AI is rolled out to their team or used across their company.
- People could pick more than one tool, so tool shares add up to more than 100%. Tool shares are out of the 1,069 people here who named at least one tool.
- Where people use AI was asked from July 20 to August 31, 2026 (734 answers here).
- Budget was asked from September 1, 2026 (446 answers here).
- Percentages are rounded to whole numbers.
- We never publish individual answers. A group only gets a page with 100 or more people, and we only compare groups of 30 or more.
- People who take an AI newsletter's quiz are more interested in AI than the average worker, so read these numbers as a benchmark of people actively working on AI, not a national average.
Last updated November 2, 2026. To cite this page: The AI Report, AI at Work Benchmark 2026, theaireport.ai/tools/benchmark.