Stop Treating AI With Regular Security Compliance (and what to do instead)
My point
I am exploring how AI security compliance represents a fundamental shift from traditional security approaches, moving from simple rule-following to a complex landscape where systems must continuously learn, adapt, and make ethical decisions in real-time. It includes practical guidance for organizations, emphasizing the need to transform everything from risk assessment to incident response, while comparing AI security compliance.
Photo by ThisisEngineering on Unsplash
Remember when your smartphone's first facial recognition feature felt like science fiction? Well, I've spent my career moving from one fascinating security challenge to another – from physical security in places like Afghanistan and Iraq to the digital realm of cybersecurity. Now, we're facing something even more incredible: making sure AI systems are safe and trustworthy, not just for companies but for everyone who uses them.
You can also find this article here on Medium.
The Dynamic Nature of AI Security Compliance
Think of it this way: moving from traditional security rules to AI security is like upgrading from a bicycle to a self-driving car. Sure, both get you from point A to B, but the self-driving car needs constant updates, learns from its environment, and must make split-second ethical decisions. Pretty different from just following traffic signs, right?
According to recent studies from PwC (PwC's 2025 Global Digital Trust), even company leaders aren't entirely confident about handling AI safely. Only 67% of CEOs feel ready for AI compliance, and the security experts (CISOs and CSOs) are even more concerned, with only 54% feeling prepared. It's like having a powerful new tool but still figuring out the instruction manual.
Breaking Down AI's Unique Challenges
Remember when the worst thing that could happen to your computer was a virus? With AI, we're dealing with much trickier problems. Imagine someone "poisoning" the data that teaches an AI system – it's like giving someone a book full of wrong information and expecting them to make good decisions.
Europe's already taking steps to handle this through the EU AI Act. Think of it as a safety manual for powerful AI systems – making sure they're as safe as the elevators we trust our lives with every day. Frameworks like the NIST AI Risk Management Framework and ISO 42001:2023 are creating a new universal language for AI governance. I will cover them and their benefits in later articles. Sure, established information security compliance standards and frameworks like ISO 27001 or the NIST 800 series are still highly relevant and needed. However, we have to think a step further ahead.
When Technical Meets Ethical
What I find most fascinating about AI security is how it brings together two worlds that rarely met before. In the “old” security world, we focused on clear-cut rules and procedures. But with AI, we're asking deeper questions: "Is this system fair to everyone?" "Could it make decisions that might accidentally hurt people?" It's not just about following rules anymore – it's about making sure our smart machines share our values.
Global Rules for a Global Technology
Just like climate change doesn't stop at borders, AI security needs worldwide cooperation. Last year alone, the United States created 25 new AI rules – that's a 56% jump from before! Europe's not far behind, showing that everyone realizes we need to work together on this.
Some Practical Tips on How to Shift Compliance Thinking
If you want to deploy or just use AI in your business or organization, here are some tips where to begin:
AI Security First Steps
Start Your AI Inventory:
Open a simple spreadsheet
List every tool your team uses
Mark those with AI features (hint: it's probably more than you think)
Note how each AI tool accesses and uses data
Create Your "AI Traffic Light" System:
🔴 Red: AI makes crucial decisions
🟡 Yellow: AI supports human decisions
🟢 Green: AI handles basic automation
Check your Security Weekly for 15 Minutes
Review unusual patterns
Check data quality
Document concerns
Share findings with your team
The best part? You can start this today, no complex tools required.
Looking Ahead and What This Means for All of Us
The future of AI security is both exciting and challenging. As Jensen Huang from NVIDIA (they make powerful chips that run AI) says, we need to balance safety with innovation.
Every time I see a SpaceX rocket land successfully, I'm reminded that what seems impossible today becomes possible with the right preparation and care. The same goes for AI security. As cognitive scientist Gary Marcus points out:
“…we need safety systems that can keep up with AI's rapid development.”
For everyone concerned about AI's future – whether you're a tech expert or just someone who uses AI-powered apps – remember that we're not just building security systems; we're creating guidelines to ensure these powerful tools make our lives better while staying true to our values.
Think of AI security compliance as the seatbelt we need – it might seem restrictive at first, but it's essential for letting us safely enjoy the incredible journey ahead. After all, the goal isn't to limit what AI can do, but to make sure it helps create the future we all want to live in.
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About me: Hi, I’m Alex! I’m writing about AI Security and Compliance. I want to steer you through the jungle of AI challenges, rules and regulations that lies ahead of us.
I also offer Consulting in Security and Compliance like ISO27001 for businesses and organizations. Reach out if you need support. http://cybrbolt.co
