Missing Chain of Custody in AI-Generated Enterprise Records
Organizations often lose critical data such as prompts, source documents, and model versions when archiving AI outputs, creating risks in legal proceedings.
With the integration of generative artificial intelligence tools into business processes, organizations are facing information management and legal production challenges stemming from the inadequacy of storing only the final output.
AI Records in Enterprise Processes
Artificial intelligence technologies are being incorporated into daily business operations for tasks such as drafting reports, summarizing meetings, and supporting compliance decisions.
Details of the Missing Chain and Model Updates
Unlike traditional documents, prompts, chat histories, and source documents are lost in AI content; model updates mean that the same commands can produce different results.
Legal Frameworks and Retention Obligations
Retention obligations under legal regulations remain valid regardless of whether the data is generated by a human or artificial intelligence.
Risk-Oriented Provenance Frameworks
It is recommended that organizations retain a minimum level of provenance data proportional to the importance of the use cases and integrate data retention requirements into procurement processes.