AI Data Ownership: CIOs Face Security & Proprietary Risks

CIOs face confusion regarding AI data types and vendor terms. Understanding input, training, output, and retrieval context data is crucial for effective governance and security. A critical unresolved issue is AI data ownership. Organizations risk losing proprietary knowledge, which can become vendor training data with every prompt and correction. Alex Bakker, an analyst at ISG, explains that every interaction with a large language model acts as a signal for vendors to fine-tune their systems. This means user interaction is essentially training data. This raises concerns about who owns this data, especially if entities like the U.S. government gain stakes in AI companies. There are three main types of data related to enterprise AI: input data, which is content put into a prompt; training data, used by vendors to train models before use; and output data, which is the generated response. Many organizations misunderstand that while they input data, terms of service often state otherwise regarding ownership. This matters because the true cost of AI can exceed initial expectations, impacting proprietary information.