How 2025 Reshaped AI and a Look at eDiscovery’s Future

February 10, 2026

How 2025 Reshaped AI and a Look at eDiscovery’s Future

Relativity’s Celia Stevenson provides insights on the direction of eDiscovery’s future from the Annual eDiscovery State of the Union panel at Relativity Fest. She reports that 2025 reshaped eDiscovery by making significant advances in data privacy, global compliance, AI adoption, and more.

Throughout 2025, AI moved from experimentation to everyday use, pulling new types of data into discovery and raising unresolved legal questions. Prompts, AI-generated outputs, and automated transcripts began appearing in real matters, often without clear governance. Legal teams need to be deliberate about how they configure and use AI tools to properly address important issues like privilege, consent, and work product.

At the same time, security threats such as prompt injection, which target large language models and other generative AI systems, have materialized. Unlike traditional vulnerabilities, these threats embed risk invisibly within documents that ignore original instructions and execute unintended actions. The rise of automated data creation is compounding the problem, as organizations struggle to identify data they didn’t even realize existed. 

Against this backdrop, roles within legal operations are evolving. Data literacy, governance, and judgment are becoming core skills. Legal professionals consider the EU Artificial Intelligence Act to be the most valuable development of the year, and they predict that Legal Data Intelligence — a framework for solving how data is organized, cleaned, and packaged — is the future of the industry. 

One of the panelists, Bob Ambrogi of LawSites, thinks AI could be the death knell for on-prem software. Ambrogi believes that generative AI for eDiscovery requires cloud-based computing power, scalability, and elasticity. As 2025 reshaped eDiscovery, the message heading into 2026 is pragmatic. While giant strides have been made toward eDiscovery innovation, we’ve learned that AI’s value in eDiscovery depends on disciplined data practices and a willingness to move toward responsible use.

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