Best Practices in AI Security & Risk

Business owners are anxious about AI—and they should be. Being cautious about a technology you don’t fully understand isn’t a weakness; it’s the right instinct.

The problem isn’t the fear itself. The problem is that the fear is too vague to act on.

When someone asks, “Is AI secure?”, they aren’t asking a technical question; they’re expressing a feeling. To make smart business decisions, you have to turn that vague anxiety into specific, named risks. Once a risk has a shape, you can actually do something about it—whether that means building guardrails, writing a policy, or avoiding a tool entirely.

What We’ll Cover:

We will break down the actual AI security threats to your business into clear, jargon-free categories. For every risk, we will cover what it really is, the realistic consequences, and how to fix it.

• Data Leakage: What happens when an employee pastes customer lists, contracts, or financial sheets into a free chatbot? (Who sees it, where it lives, and who gets sued).
• Training Contamination: Is OpenAI training its models on your data? We’ll look at the hidden differences between free and paid tiers that most owners miss.
• Accidental Destruction: Why bad prompts are increasingly deleting rows, files, or entire databases as AI gets more system access—and how to keep a “human-in-the-loop.”
• Account & Credential Compromise: Guarding against a new attack surface, including phishing attacks targeting AI logins and malicious prompts hidden in shared documents.
• Dependency & Outages: The hidden risk of building critical workflows around a single vendor. What happens to your business if your primary AI tool goes down for six hours?
• Compliance & Regulations: How AI tools quietly trigger massive data disclosure problems for businesses handling HIPAA, financial, or legal data.

The Goal: You will leave this webinar able to say: “Here is the exact AI risk I was worried about, and here is the practical step I am taking to fix it.”