What is AI Security?
Have you ever stopped to think how secure your use of AI tools really is? What about your entire organization? With multiple employees using generative AI to move faster, how do you ensure they’re doing it responsibly? What if someone uploads sensitive data into a public model? How do you track it, or remove it?
AI security is the practice of protecting AI systems, the data they use, and the outputs they generate. Done right, it aligns with your organization's governance, privacy, and compliance standards. Done poorly, it’s a liability waiting to happen.
The Risks of Ignoring AI Security
Let’s not overcomplicate this: if you’re feeding sensitive business data into a generative AI tool with no guardrails, it could be leaked or compromised. Gartner outlines two of the biggest risks:
- Compromised data privacy through unchecked input sharing or overexposure.
- Inaccurate or harmful outputs—sometimes biased, hallucinatory, or misleading.
IBM adds that attackers can manipulate prompts to "jailbreak" AI guardrails, coaxing models into disallowed responses that could spread misinformation, expose secrets, or damage brand trust.
Why Governance and Compliance Matter
Governance may sound like a buzzkill, but it’s actually your best defense. Think of it like giving your teen a car—with no rules, no training, no license. Something is going to go wrong.
Governance ensures AI is used intentionally and safely. Compliance ensures you can prove it. There’s no one-size-fits-all approach to AI governance, but these frameworks provide clear starting points.
Top institutions like NIST, ISO, Forrester, and Gartner have laid out models for doing this right:
Regardless of framework, the goal is the same: reduce risk, maintain trust, and create confidence in how AI is used across the business.
7 Steps to Strengthen AI Securely
Once you’ve chosen a governance framework, these steps help operationalize it day-to-day:
- Set policies and accountability: Define what responsible AI use means for your org. Appoint a governance lead.
- Inventory your tools: Track all AI applications in use. Flag shadow AI. Classify by risk.
- Secure your data: Apply classification, encryption, and strict access controls. Don’t expose private data to public AI.
- Control access: Use role-based permissions. Log all AI activity. Ensure humans are still accountable.
- Establish guardrails: Use filters, approval workflows, and prompt limits. Block unsafe outputs.
- Monitor continuously: Watch for drift, bias, or attack patterns. Tie alerts into your SOC workflow.
- Train your people: Teach them how to use AI responsibly. Build a "trust but verify" culture.
How SOC 2 Strengthens AI Security and Compliance
If you're in FinServ or serve clients who are, SOC 2 certification is critical. It proves that your systems, including your AI tools, are secure, private, and governed. Even if you’re not in finance, SOC 2 alignment demonstrates enterprise-level security and builds confidence.
Integrating AI into your SOC 2 audit scope sends a strong message: we’re not just using AI, we’re using it responsibly.
How Opal by Optimizely Puts Security First
Opal is Optimizely’s generative AI platform for marketing teams. It enables automation without sacrificing governance. Here’s how:
- Access controls and audit trails: Limit who can do what. Track every AI decision.
- Data privacy: Inputs are processed in-memory and never retained or reused to train models.
- Content ownership: You own what Opal generates. Humans remain in the loop.
- RAG (Retrieval-Augmented Generation): Used to improve accuracy and limit hallucinations.
Learn more about our Optimizely partnership
Final Thought: Responsible AI Is a Competitive Advantage
AI done wrong creates risk. AI done right unlocks speed, trust, and differentiation.
If your business is serious about scaling AI, make sure governance and compliance come along for the ride. The C2 Group can help you map out what safe, secure AI adoption looks like today and as you grow.