Discernis says getting the workflow right and preparing for what’s coming is key to success in using AI in corporate investigations.

In their post titled (wait for it!) AI in Corporate Investigations: Getting the Workflow Right and Preparing for What’s Coming, available here) Discernis references parts I and II in this series covered the case for AI in corporate investigations, discussing the core capabilities that matter, legal and ethical guardrails, defensibility, platform selection, and the confidentiality risks that don’t get enough attention.

This final post tackles the practical and forward-looking side: 

• How do you structure AI investigations to work well?
• What is the regulatory environment telling you?
• What should you do right now to be ready? 

One of the most important framing decisions in-house counsel can make is this: AI is an investigative intelligence tool, not an automation tool. The distinction shapes how you structure the work, who is accountable, and how you explain your methodology if it’s ever challenged.

In practice, AI excels at the parts of an investigation that are most resource-intensive and least suited to human review at scale: processing large document sets, identifying communication patterns, surfacing unexpected connections, and classifying relevance across thousands of records in a fraction of the time it would take human reviewers. What it cannot do is exercise the legal judgment that gives those findings meaning.

So, what should the structure of an AI-assisted investigation look like? What operational principles are worth building into your workflow? And what’s a practical checklist for what to do now? Find out here, it’s only one click! Clicking is an easy workflow to get right! 😉

So, what do you think? How is your organization leveraging AI in corporate investigations? Please share any comments you might have or if you’d like to know more about a particular topic.

Image created using ChatGPT, using the term “robot lawyer conducting an internal corporate investigation using AI”.

Disclosure: Discernis is an Educational Partner and sponsor of eDiscovery Today

Disclaimer: The views represented herein are exclusively the views of the author, and do not necessarily represent the views held by my employer, my partners or my clients. eDiscovery Today is made available solely for educational purposes to provide general information about general eDiscovery principles and not to provide specific legal advice applicable to any particular circumstance. eDiscovery Today should not be used as a substitute for competent legal advice from a lawyer you have retained and who has agreed to represent you.