Everyone wants AI agents right now. Faster workflows, less manual work, more automation. What’s not to like? The problem: A lot of companies are rolling out agentic AI with governance frameworks built for chatbots and traditional software, but those frameworks weren’t designed for autonomous systems that make decisions and take action on their own.
In her latest article for The Heller Report, CM Law Partner and Technology Practice Chair Reiko Feaver explains why AI agents represent a different category of risk entirely. Traditional software usually breaks when someone bypasses its rules. AI agents can create problems while doing exactly what they were told to do—the result of bad instructions, compromised inputs, or flawed context.
That becomes a bigger issue when agents can simultaneously access databases, send communications, interact across systems, and trigger downstream actions. One bad input doesn’t just create one bad result; it can start a chain reaction.
Reiko lays out four shifts organizations should make before they hand over the keys:
- Map risks before deployment
• Limit access aggressively
• Monitor behavior, not just permissions
• Put actual humans on the hook for oversight
Bottom line: Organizations rushing to deploy AI agents without rethinking governance may discover that “move fast and automate things” becomes a lot less fun after the incident report arrives.
If you have questions about AI agents and your organization, please contact Reiko directly at rfeaver@cm.law.
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