How are companies handling AI audits as their AI systems keep growing?

I've been looking into how companies are approaching artificial intelligence auditing, and one thing that stands out is how difficult it can become once an organization has more than a few AI systems.

A basic audit might involve checking:

• What AI systems are being used
• Who owns them
• What risks they create
• Whether they fall into specific regulatory categories
• What documentation exists
• What evidence supports compliance
• Whether monitoring and human oversight are actually in place

The problem is that these things can change over time.

For organizations dealing with high risk AI systems, maintaining documentation and evidence manually can become particularly challenging. That's why I'm interested in the idea of using an AI audit platform rather than treating auditing as a once-a-year checklist.

It also seems like AI auditing needs to be connected with broader AI Governance and day-to-day AI Compliance Operation, rather than being handled as a completely separate activity.

For example:

AI inventory → risk assessment → requirements → controls → evidence → monitoring → audit → remediation

That seems much more practical than scrambling to collect everything when an audit is already scheduled.

I came across AnnexOps while researching this approach. They have a platform focused on AI auditing and compliance readiness:

https://annexops.com/ai-audit-platform/

Curious how others are handling this. Are you using a dedicated AI compliance/auditing platform, or are spreadsheets, documentation systems, and internal processes still working for your organization?