When AI Becomes a System of Record: Why Evidence Will Define Liability (www.aivojournal.org)

The article emphasizes the evolving role of AI outputs within organizations, highlighting their transition from mere advisory tools to becoming official systems of record. As AI-generated data increasingly influences business decisions, its implications for liability and governance cannot be overstated. The piece argues that most organizations have not designed their AI systems to meet the evidentiary standards expected from traditional records, which poses significant risks when outputs are questioned. Once AI outputs are used to justify decisions or actions, they become institutional artifacts requiring traceability and accountability, fundamentally altering liability considerations. This shift presents new challenges for organizations. As AI systems move from generating suggestions to making autonomous decisions—like updating records or triggering financial actions—they must adhere to established governance protocols, including change control and audit trails. The article warns that reliance on model accuracy as a defense is insufficient; organizations must proactively capture evidence of AI actions to mitigate liability risks. It concludes that those entities that can effectively reconstruct AI outputs and maintain clear records will be better positioned to navigate the evolving landscape of AI governance and accountability.