We talk about generative AI a lot, but not that much about generative AI created content as discoverable evidence. Cimplifi discusses that here!

In their post titled (wait for it!) Taming Modern Data Challenges: Generative AI Created Content (available here), Cimplifi discusses that perhaps the newest modern data challenge is the explosion of generative AI content in organizations. While most of the discussion of GenAI in relation to eDiscovery relates to how GenAI can streamline review and many other workflows within discovery, there isn’t much discussion about the growing volumes of generative AI-created content within organizations through the use of tools like ChatGPT, Gemini, Claude, and Microsoft Copilot.

AI can generate a wide spectrum of electronically stored information (ESI). Examples include conversation logs with chatbots, first drafts of contracts or emails, code snippets created by developer tools, and marketing copy produced at scale. Some of this content may be produced within your organization through approved platforms; for example, Microsoft Copilot may have been integrated into your organization’s M365 environment. However, AI-generated content can also come from shadow IT usage, where employees turn to free or consumer versions of ChatGPT or other chatbots without corporate oversight. According to one study, 85% of IT decision-makers say employees are adopting AI tools before IT can even assess them.

So, what are examples of when generative AI created content could become relevant in litigation? What are the discovery challenges associated with it? And what should collection strategies consider from an eDiscovery standpoint? Find out here, it’s just one click! Even your GenAI chatbot thinks it’s a good idea! 😉

So, what do you think? How is your organization taming modern data challenges in eDiscovery? Please share any comments you might have or if you’d like to know more about a particular topic.

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