Data report
State of AI in capital markets
What 15 documented AI deployments by 10 organizations in capital markets say about who uses the AI, how far it acts on its own and how often the result is proven, set against the whole library.
Computed live from the library on 12 November 2026. By Len Debets.
Who works with the AI
0% of public deployments in capital markets put the AI in front of customers directly, against 31% across the library. The rest support employees or run inside a back office process.
- Employee facing9
- Back office6
How far the AI acts on its own
67% of public deployments in capital markets belong to use cases where the AI completes work itself (a supervised or autonomous agent, or an agentic workflow), against 63% across the library.
- Copilot11
- Supervised agent3
- Assist1
Where the deployments come from
53% of the public deployments in capital markets are by organizations in North America. 53% date from 2025 or 2026, against 57% across the library.
- North America8
- Europe3
- Global2
- Asia Pacific1
- Latin America1
How often the result is proven
73% of public deployments in capital markets disclose a measurable outcome, against 61% across the library. Of the 11 reported metrics, 3 came from a vendor rather than from the organization itself.
- Organization8
- Vendor3
The most documented use cases in capital markets
Ranked by the number of capital markets organizations with a public deployment.
- AI for settlement fail prediction and post trade exception management3 organizations
- AI for market abuse surveillance alert triage2 organizations
- AI summaries of investment research and the house view2 organizations
- AI agent for data quality monitoring and observability1 organization
- AI assistant for employee onboarding1 organization
- AI coding assistant for software developers1 organization
- AI for business onboarding (KYB) and beneficial ownership discovery1 organization
- AI for legacy code modernization1 organization
- AI for payment investigations and exceptions1 organization
- Generative AI copilot for internal audit1 organization
Frequently asked questions
- How is AI used in capital markets?
- The most documented AI use cases in capital markets are AI for settlement fail prediction and post trade exception management, AI for market abuse surveillance alert triage and AI summaries of investment research and the house view, across 15 public deployments by 10 organizations in the Blits.ai AI Use Case Library. 0% of public deployments in capital markets put the AI in front of customers directly, against 31% across the library. The rest support employees or run inside a back office process.
- How many AI deployments in capital markets use AI agents?
- 67% of public deployments in capital markets belong to use cases where the AI completes work itself (a supervised or autonomous agent, or an agentic workflow), against 63% across the library.
- How often do capital markets organizations prove the results of AI?
- 73% of public deployments in capital markets disclose a measurable outcome, against 61% across the library. Of the 11 reported metrics, 3 came from a vendor rather than from the organization itself.
About this report
This report counts every public deployment by an organization in capital markets, whatever the use case, and sets it against all 1921 public deployments in the library. The industry hub counts only the use cases tagged with this industry, so its totals can be lower. Every figure is computed with the rules on the methodology page, from the open data (CC BY 4.0). The sample reflects what organizations choose to publish, which skews toward large organizations and successful projects.
See also all AI use cases in capital markets, the EU AI Act in capital markets and the State of AI Use Cases across every industry.