Company AI Risk Explorer
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Welcome to the Company AI Risk Explorer

This tool maps what large global companies say in public about AI risk. We reviewed public documents from roughly 200 of the world's largest companies. We coded every risk they acknowledge against the AI Risk Repository taxonomy.

Filter by company, sector, AI role, or risk. Compare what companies acknowledge against expert ratings of severity, sector vulnerability, and role responsibility.

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Companies × risks

PNC Financial Services

PNC Financial Services deploys generative AI platforms across the organisation, including Microsoft Copilot, and has built specialised ML systems for healthcare claims prediction and fraud detection. Its leadership holds a chair role in the Financial Services Sector Coordinating Council, contributing to sector-level AI governance.

We reviewed 3 public documents from PNC Financial Services and found it acknowledges 6 of 24 AI risks, including fraud & scams and loss of privacy.

Sector: Finance and Insurance

Roles: AI deployer

AI risks PNC Financial Services acknowledges

  • Fraud & scams: “The effectiveness of these efforts may be enhanced using AI. These efforts may be to obtain access to confidential information, often with the intent of stealing from or defrauding us or our customers” (PNC Financial Services 2025 Annual Report)
  • Loss of privacy: “AI poses unique privacy challenges: the risk of feeding personal information into an AI system” (PNC Protecting Customer Privacy & Security)
  • Weapons & cyberattacks: “efforts by bad actors to engage in various types of cyber attacks and breaches... pose serious risks to our business and reputation... The effectiveness of these efforts may be enhanced using AI.” (PNC Financial Services 2025 Annual Report)
  • Capability & robustness: “Enhanced use of automation may present its own risks. Automated systems may themselves experience outages or problems... Bad, missing or anomalous data can adversely affect the functioning of such tools.” (PNC Financial Services 2025 Annual Report)
  • Discrimination: “AI poses unique privacy challenges: ... the risk that AI could identify or treat an individual differently based on the available information.” (PNC Protecting Customer Privacy & Security)
  • Transparency & interpretability: “because of the complex way in which the many variables in AI/machine learning models interact, the results of these models are often less interpretable than traditional statistical models.” (PNC Financial Services 2025 Annual Report)

Documents we reviewed