Author: Alex Morgan
-
Why AI Governance, Compliance, and Liability Are Closely Connected
Artificial intelligence governance, regulatory compliance, and legal liability are often discussed as separate topics, but in practice they are closely connected. Organizations deploying AI systems must understand how governance structures influence regulatory compliance and how both affect potential liability when automated systems produce harmful outcomes. As artificial intelligence becomes more deeply integrated into business operations,…
-
What Due Diligence Should Companies Perform Before Using AI Vendors?
Many organizations deploy artificial intelligence systems through third-party vendors rather than developing the technology internally. While vendor-provided AI tools can accelerate adoption, they also introduce new legal and operational risks. Companies relying on external AI providers must therefore conduct appropriate due diligence before integrating these systems into business operations. Vendor due diligence helps organizations evaluate…
-
What Types of Insurance Cover AI-Related Lawsuits?
As artificial intelligence systems influence more business decisions, organizations increasingly ask whether their insurance policies cover lawsuits involving AI-driven outcomes. Because automated systems can affect hiring decisions, lending approvals, healthcare recommendations, and financial analysis, disputes involving artificial intelligence may trigger several different types of insurance coverage. Understanding which policies may respond to AI-related lawsuits helps…
-
Why Human Oversight Matters in AI Governance
Artificial intelligence systems increasingly influence decisions involving hiring, lending, insurance underwriting, healthcare recommendations, and financial risk analysis. As these technologies become more widely used, regulators and policymakers consistently emphasize the importance of human oversight in AI governance frameworks. Human oversight refers to the mechanisms organizations use to monitor automated systems, review important AI-driven decisions, and…
-
How AI Model Risk Is Evaluated in Legal and Compliance Reviews
As artificial intelligence systems become increasingly integrated into business decision-making, organizations are placing greater emphasis on evaluating the risks associated with AI models. Model risk refers to the potential for an artificial intelligence system to produce inaccurate, biased, or unreliable outputs that could lead to financial loss, regulatory scrutiny, or legal liability. Evaluating AI model…
-
Who Investigates AI Failures When Harm Occurs?
When artificial intelligence systems produce harmful outcomes, organizations must often investigate what went wrong and determine whether corrective action is required. AI failures can trigger internal reviews, regulatory investigations, civil lawsuits, or insurance claims depending on the nature of the harm. Understanding who investigates AI failures and how those investigations unfold is an important part…
-
Do Companies Need Insurance for AI Liability?
As artificial intelligence systems become more integrated into business operations, organizations increasingly evaluate whether traditional insurance coverage adequately protects them from AI-related risks. One question frequently raised by executives and risk managers is whether companies need specialized insurance coverage for AI liability. Although artificial intelligence does not automatically require a new category of insurance, many…
-
How Companies Can Prepare for Emerging AI Regulations
Artificial intelligence regulation is evolving rapidly as governments around the world attempt to address the risks associated with automated decision systems. While many regulatory frameworks are still under development, organizations deploying AI technologies increasingly recognize the need to prepare for emerging compliance requirements. Companies that proactively evaluate AI risk and implement governance structures may be…
-
What Is an AI Accountability Framework?
As artificial intelligence systems become more deeply integrated into business operations, organizations increasingly adopt governance structures designed to monitor how these systems operate. One concept that frequently appears in regulatory discussions and corporate governance policies is the idea of an AI accountability framework. An AI accountability framework refers to the set of policies, procedures, and…
-
What Legal Standards Apply When AI Systems Cause Harm?
As artificial intelligence systems increasingly influence real-world decisions, courts are beginning to evaluate how existing legal standards apply when AI-driven outcomes cause harm. While many discussions focus on emerging AI regulation, most legal disputes involving artificial intelligence are currently resolved using traditional legal doctrines. When individuals or organizations claim that an AI system caused harm,…