Credit: Rafael Henrique/Adobe StockWhere Do All the Prompts Go? Generative AI and the Genesis of a New Emerging Data Paradox
While there are dozens of considerations for organizations to address when evaluating and implementing Copilot or any generative AI tool, one lesser-known issue is how interactions with and output from enterprise generative AI tools are creating an entirely new set of data that could ultimately come into scope in e-discovery.
December 13, 2024 at 11:20 AM
5 minute read
A little over a year following Copilot’s release and Microsoft has already begun to announce round two of updates and integrations. As with any significant changes, especially involving artificial intelligence, an array of new complexities and challenges are expected for collection, storage and understanding of the data generated by generative AI tools.
Microsoft Copilot adoption continues growing quickly among enterprises, with some early estimates indicating that more than half of organizations are exploring its use, and approximately one-third are already using it within their Microsoft 365 environments. While there are dozens of considerations for organizations to address when evaluating and implementing Copilot or any generative AI tool, one lesser-known issue is how interactions with and output from enterprise generative AI tools are creating an entirely new set of data that could ultimately come into scope in e-discovery.
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