What is Real-Time AI Compliance?
What is Real-Time AI Compliance?
Real-time AI compliance is the practice of applying compliance requirements while an AI system is operating, rather than relying only on reviews before deployment or after the fact. It allows organizations to check AI activity against applicable rules as that activity occurs and respond when a requirement is not met.
Those requirements can come from regulations, company policies, and security controls. How they are applied depends on the AI system and the rules involved. For AI-generated communications, real-time compliance can include checking a message while it is still in the send path, so an issue can be addressed before the message reaches its recipient.
How it works
Compliance requirements become controls that operate alongside the AI system.
Requirement
Define the regulation, company policy, or security control that applies.
Check
Apply the requirement to the relevant AI content or behavior as it occurs.
Action
Determine what should happen when the requirement is or is not met.
Evidence
Record the decision, the requirement that applied, and the action taken.
Real-time compliance applies requirements while an AI system is operating, rather than relying only on pre-deployment checks or later reviews. This gives organizations a chance to address a compliance issue when it occurs, before AI-generated content is sent or an action is completed.
What it is not
Related approaches,
and where they stop.
AI governance sets the broader framework
Real-time compliance applies requirements during operation.
Pre-deployment testing checks the system before use
Pre-deployment testing checks the system before use.
Monitoring provides visibility
Real-time compliance can also trigger action.
Auditing examines evidence
Real-time compliance can produce evidence as activity occurs.
Why now
AI systems operate continuously.
Compliance needs to operate at the same pace.
As organizations use AI to generate content and carry out a wider range of tasks, the volume of activity subject to compliance requirements can grow quickly.
Traditional reviews remain important, but they often happen before or after an AI system is used. Real-time compliance adds checks while the system is operating. This allows compliance issues to be addressed as they happen, rather than discovered later.
FAQ
Common questions.
What does real-time AI compliance mean?
Real-time AI compliance means applying compliance requirements while an AI system is operating. Instead of checking compliance only before deployment or reviewing activity afterward, relevant requirements can be applied when the AI produces content or performs an action. This allows an organization to identify an issue and determine what should happen while the activity is still taking place.
How does real-time AI compliance work?
Real-time AI compliance turns applicable requirements into controls that can operate alongside an AI system. A control checks the relevant content or behavior when it occurs and determines what should happen based on the requirement. Depending on the use case, that could mean allowing the activity to proceed, correcting an issue, stopping it, or sending it for human review.
What is the difference between real-time
AI compliance and AI governance?
AI governance is the broader framework an organization uses to manage how AI is developed, deployed, and used. It can define policies, assign responsibilities, establish review processes, and set expectations for how AI should operate. Real-time AI compliance focuses on making sure relevant requirements are followed while an AI system is actually in use. This allows compliance controls to respond to issues when they occur, rather than relying only on checks before deployment or reviews afterward.
Is real-time AI compliance the same as monitoring?
No. Monitoring observes an AI system and provides visibility into its activity, performance, or behavior. It can help an organization identify problems, investigate unusual activity, and understand how a system is operating over time. Real-time AI compliance serves a different purpose by applying specific requirements while the system is in use. When an issue is identified, a control can determine how that activity should be handled based on the rule that applies.
What is the difference between real-time
AI compliance and runtime enforcement?
Real-time AI compliance is the broader practice of applying compliance requirements while AI systems are operating. It describes the goal of identifying and addressing compliance issues as relevant activity occurs, rather than relying solely on checks before use or reviews afterward.
Runtime enforcement is a way to put that approach into practice. It applies written rules to AI behavior while the system is operating and determines what should happen when those rules are not met. For AI-generated communications, that can mean enforcing a rule while a message is still in the send path, so an issue can be addressed before the message reaches its recipient.
Why is real-time compliance important
for AI-generated communications?
AI systems can generate customer-facing communications continuously and at a volume that makes reviewing every message manually difficult. Those communications may still need to follow regulations, company policies, and security controls, regardless of whether they were written by a person or generated by AI.
Real-time compliance allows those requirements to be applied while a message is still in the send path. A message can be checked for issues such as prohibited claims, missing disclosures, or sensitive information before it reaches the recipient. This gives organizations a way to address compliance issues within the communication process itself, while there is still an opportunity to act.