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01 · Use cases— The evidence

NASDAQ

3 documented AI deployments at NASDAQ, across 1 industry. Each one links to the public source it was taken from.

New York City, Sweden · Founded 1971 · nasdaq.com · WikipediaSource: Wikidata, 2026-11-01

3
deployments
on record
1
industry
Finance
0%
use AI agents
0 of these
20 May 2026
latest source date
2 report a measured outcome
§ 1

Public AI record

NASDAQ has 3 documented public AI cases on the hub, too few for a score. Document automation is common among peers but not yet documented at NASDAQ.

Low confidenceBased on 3 public cases · updated 10 Nov 2026

A record score appears once NASDAQ has 5 documented public cases. The peer comparison below already uses what is on record.

First documented case Feb 2025, latest May 2026. Cloud providers named: AWS, Microsoft.

§ 2

Compared with peers

Against 14 other finance companies on the hub.

What peers document

  1. Document automation6 of 14 peers
    43%
  2. Fraud detection4 of 14 peers · here too
    29%
  3. Customer service automation3 of 14 peers
    21%
  4. Employee productivity3 of 14 peers
    21%
4 of 6 patterns

Gaps against the industry

Stack and approach vs peers
  • Peer cases name AWS 36%, Microsoft 34%, GCP 28%.
  • AI agents: 0% of NASDAQ's cases vs 18% for peers.
  • Cases from the last 12 months: 67% vs 37% for peers.
§ 3

Deployments

3 deployments at NASDAQ, newest first.

  • 20 May 2026
    Finance

    Nasdaq integrated Microsoft Foundry and Azure OpenAI for AI-powered document summarization and workflow automation in Boardvantage

    NASDAQ · Legal document summarization · Microsoft

    Nasdaq re-architected its Boardvantage platform on Azure, using Azure Kubernetes Service and Azure Database for PostgreSQL/Azure Database for MySQL as the data foundation. Microsoft Foundry and Azure OpenAI were integrated to provide AI-powered document summarization and workflow automation for board materials.

    −60%
    reading time
  • 14 Jan 2026
    Finance

    Financial institutions advance mission-critical workloads and Agentic AI at re:Invent 2025

    NASDAQ · Fraud detection · AWS

    At AWS re:Invent 2025, multiple financial institutions including NASDAQ, Visa, National Australia Bank, BlackRock, and Allianz Technology SE showcased advanced implementations of AI agents and mission-critical cloud workloads using AWS technologies. Financial institutions are rapidly shifting from debating AI adoption to deploying agentic AI for competitive advantage, with developer productivity significantly improved. Use cases showcased include real-time trading assistants, fraud detection, claims processing, compliance automation, and customer service enhancements using Amazon Bedrock AgentCore and other AWS AI tools. AWS provided enhanced infrastructure and service capabilities such as multi-region resiliency, data masking, catalog federation, and Amazon Nova Forge for custom frontier models. Several financial institutions demonstrated multi-agent architectures to automate insurance claims and customer service workflows, reducing processing times by up to 80%. Advanced AI agents are integrated with policy controls for regulatory compliance and auditability, supporting trading, payments, and wealth management applications. AWS innovations like Amazon Connect enhancements and AI-powered recommendations enable personalized customer experiences and operational efficiencies.

    Scaled Production

    −80%
    time
  • 19 Feb 2025
    Finance

    Automated Reasoning Checks in Amazon Bedrock Guardrails for Financial Services

    NASDAQ · Risk assessment · AWS

    AWS Financial Services customers like NASDAQ, State Bank of India, and Bridgewater use Amazon Bedrock Guardrails Automated Reasoning checks to enhance transparency and compliance in financial workflows involving foundation models. Automated Reasoning checks provide deterministic validation of generative AI outputs against logical rules encoded from source documentation, reducing risk of hallucinations. Use cases include insurance underwriting rule validation, legal triaging of claims, and claims processing, with audit trails and mathematical proof ensuring regulatory compliance and trust. This deterministic approach supports reproducible decision support, improves confidence in AI outputs, and safeguards regulated financial workflows against inaccuracies.

§ 4

What it builds

Fraud detection is the most common pattern in these deployments: 1.

§ 5

Cloud providers named

AWS is named in 2 of these deployments.

  1. AWS67% of these
    2
  2. Microsoft33% of these
    1
§ 6

Industries

All of these deployments are in Finance.

Compare industries

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