company

Mastercard

Financial Services / Payments Technology
75Good
Aio Composite Score
Confidence
ApplicationHeavy
high
ImpactMixed
medium
OpennessTransparent
high
Mastercard is a deeply committed and long-standing AI adopter, deploying machine learning, neural networks, natural-language processing, and generative AI across fraud detection, transaction security, personalization, and business payments. The company has established formal AI governance infrastructure including an AI Governance Council, a partnership with Credo AI for scalable GenAI governance, and a Chief AI and Data Officer role, and publicly discloses its AI activities extensively in SEC filings and public communications. Two rounds of layoffs (approximately 3% in 2024 and 4% in 2026) have been reported, though neither has been explicitly linked by the company to AI-driven automation — the 2026 restructuring is described as a strategic business review, with no direct causal link to AI established in available sources. Mastercard's public posture is consistently transparent, with governance and responsible AI messaging corroborated by third-party partnerships, filings, and independent reporting.
Application
How is AI being used?
Heavy
high
Mastercard deploys AI extensively across fraud detection, transaction processing, personalization, business payments, and agentic commerce, with AI…
Impact
How have people been affected?
Mixed
medium
Mastercard reports strong positive outcomes from AI in fraud prevention (billions blocked, doubled compromised card detection), and no customer-harm…
Openness
Company honesty about AI use.
Transparent
high
Mastercard's public narrative — extensive AI use, formal governance, human oversight, and responsible AI principles — is corroborated by SEC filings,…
AI Tools & Platforms Detected
Credo AI (AI governance platform)Generative AI (various LLMs including Copilot, Gemini, ChatGPT integrations via Agent Pay)Machine learning modelsNeural networksNatural-language processingDecision Management PlatformRecorded Future (cybersecurity intelligence)Agentic AI / Agent Pay
AI Hiringmoderate
30AI roles/ 25903 total
Lead AI EngineerPrincipal AI EngineerVice President, Business Security Officer for Data and AISenior Counsel, Privacy, AI and Data ResponsibilityMachine Learning Engineer, Connections AI Labs
Key Evidence (9)
Mastercard's 10-K explicitly names 'Data and AI' as a core business pillar, listing machine learning, NLP, neural networks, and generative AI as deployed technologies across products, services, and internal operations.
2026-02-11
sec filingSource ↗
10-K also references 'Consulting and agentic solutions' and 'Advanced analytics and AI solutions' as named product/service lines, with AI Governance processes described as embedded across all products.
2025-02-12
sec filingSource ↗
Mastercard partnered with Credo AI to build a scalable GenAI governance system; the Credo AI Platform's AI Registry and Vendor Registry are used to manage hundreds of GenAI use cases and ensure alignment with governance frameworks.
web searchSource ↗
Mastercard claims its generative AI deployment has doubled detection rates of compromised payment cards and boosted overall fraud detection rates by 20% to up to 300%, blocking billions in fraud annually.
web searchSource ↗
Mastercard established an AI Governance Council five years ago; MIT Sloan article documents that the company's executive stated generative AI deployments will make 'extensive use of humans in the loop, perhaps through reinforcement learning with human feedback.'
web searchSource ↗
Mastercard's Chief AI and Data Officer Greg Ulrich publicly describes the company's 'hub and spoke' AI model and long history of AI use in an a16z podcast, demonstrating consistent and open public communication about AI strategy.
web searchSource ↗
What insider reports could clarify
  • How are AI-generated fraud decisions reviewed before affecting a customer's transaction or account?
  • Have any specific roles or teams been explicitly replaced by AI tooling rather than re-hired?
  • How does Mastercard's AI Governance Council evaluate and reject proposed AI use cases in practice?
  • Do customer-facing AI outputs (e.g., personalization, portfolio insights) include disclosure that AI was used?
  • How are employees informed if their work is being automated or augmented by AI tools internally?
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