What is the role of AI deployers in risk management?

• A. Deployers are responsible for managing risks in their environment
• B. Deployers create risk assessment frameworks for vendors
• C. Deployers regulate external APIs
• D. Deployers only collect data

Answer: (A)

The main idea is that the person or team who actually operates and uses the AI system is responsible for managing the risks in that environment. Deployers must identify potential risks that could arise from data handling, model behavior, security, privacy, and governance, and put in place controls to mitigate them. This includes ongoing monitoring for issues like data drift or biased outputs, implementing incident response and rollback plans, ensuring proper access controls and data protection, and adapting risk strategies as the system or environment changes. In practice, this ownership means coordinating with security, privacy, governance, and procurement functions to keep risk in check where the AI is deployed.

While collecting data is a part of using AI, risk management is broader and ongoing—it’s about controlling and reducing potential harms and compliance gaps throughout the deployment lifecycle, not just gathering information. Creating risk assessment frameworks for vendors falls under vendor risk management and procurement processes, not the deployer’s primary role. Regulating external APIs is typically handled by regulators or API providers, not by the deployer.