# AI Security 101: Best Practices & Pitfalls

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AI is transforming the way businesses operate, from **AI-powered tools** to **embedded AI in business apps**, and now **AI Agents that can perform tasks autonomously**. But as AI adoption grows, so do concerns around security.

In this lesson, we’re going to break down the **major security considerations** for each type of AI deployment and discuss best practices for ensuring AI is used safely in your organization.

We’ll also cover how **bad actors** can use AI for **phishing attacks and cyber threats**, and we’ll separate fact from fiction when it comes to AI-related security fears.

By the end of this session, you’ll understand how to **secure AI applications, AI Agents, and embedded AI inside business software**, while also protecting your company’s data, workflows, and systems.

#### **Understanding AI Security Across Different Deployments**

AI is being deployed in three major ways:

1. **AI Apps** – Standalone AI-powered tools like ChatGPT, Jasper AI, and Midjourney
2. **Embedded AI** – AI features inside existing software, like Microsoft Copilot or AI-powered CRM assistants
3. **AI Agents** – Fully autonomous AI systems that can interact with applications and perform business tasks

Each of these deployments has its **own security risks**, and it’s important to understand the differences.

**Security Risks in AI Apps**

AI applications—like ChatGPT, Jasper AI, and image generation tools—are great for productivity, but they also come with **data security risks** if not used properly.

One of the biggest concerns is **data leakage**. Many consumer-grade AI models, including the free version of ChatGPT, **train on the data that users input**. This means that if an employee **uploads confidential documents**, proprietary code, or sensitive customer information, that data could be stored and used to improve future AI responses—which is a massive security risk.

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The good news is that **Enterprise AI solutions**, like **OpenAI’s business offering**, **do not train on company data**. If your organization is using AI at scale, always ensure that your AI tools are being used **under an enterprise license** to protect sensitive information.

Bad actors can also use AI to **improve phishing attacks**, generating **more convincing scam emails** with perfect grammar and context-aware messaging. This means organizations must train employees to recognize **AI-generated phishing attempts** and strengthen their cybersecurity protocols.

**Security Risks in Embedded AI**

Embedded AI—AI built into existing software like CRMs, spreadsheets, and productivity apps—has a **lower risk** of data leakage because it operates **within the security framework of the host application**.

However, there are still concerns. Since AI is often used to **summarize documents, draft emails, or provide insights**, employees may **inadvertently expose sensitive data** by requesting AI to process information that **wasn’t meant to be shared or analyzed in certain ways**.

For example, if an AI-powered CRM **generates customer insights**, what controls are in place to prevent unauthorized employees from accessing private customer data?

Organizations must set up **role-based access controls (RBAC)** to ensure AI-powered insights are only available to **the right users**.

Another risk is **misuse of AI-generated content**. Since AI is designed to predict responses, it can sometimes **make up information or misinterpret context**. Employees need to **verify AI-generated reports, summaries, or financial projections** before taking action.

**Security Risks in AI Agents**

AI Agents are the most powerful form of AI deployment because they don’t just assist users—they **take action** inside business systems.

Because of this, they also carry **the highest level of security risk** if not deployed correctly.

One of the biggest mistakes businesses make is **giving AI Agents too much access** to applications, databases, or communication channels.

For example, an AI Agent designed to **schedule sales meetings** should only have:

* Access to the **sales team’s calendar**
* The ability to **send emails on behalf of the sales team**
* Access to a **CRM system to update lead statuses**

But it **should not** have access to **finance, HR records, or system-wide administration controls**.

The best practice here is to **treat AI Agents like employees**—only giving them **the permissions they need** to perform their assigned tasks.

This is where platforms like **Raia** come in. Raia allows businesses to **train, test, and control AI Agents**, ensuring they operate within defined guardrails. Organizations can set up access controls, monitor AI activity, and prevent unauthorized actions.

AI Agents also need **secure authentication methods**. Instead of giving them full system access, companies should use:

* **API authentication** to limit the AI’s capabilities
* **OAuth permissions** to restrict data access
* **Audit logs** to track every action the AI takes

By treating AI Agents like **external software applications** instead of open-ended assistants, businesses can ensure they operate safely.

#### **The Biggest AI Security Myths & Misconceptions**

There’s a lot of fear around AI security, but **many concerns are overblown or misunderstood**.

One of the biggest misconceptions is that **AI models store and execute commands like a human brain**. In reality, **language models are read-only databases**—they **do not have independent memory** unless they are built into an application with persistent storage.

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This means **AI cannot execute tasks on its own** unless it is **connected to a system via software**. AI isn’t making unauthorized decisions—it’s simply following instructions from the applications it’s embedded in.

So, while AI security is important, it’s not fundamentally different from **securing any other SaaS product**. The real security risks come from **how AI is integrated, how much access it’s given, and how it’s monitored.**

#### **Best Practices for AI Security**

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To help businesses deploy AI safely, here are some best practices to follow:

1. **Use an Enterprise AI License**\
   Always ensure employees use **enterprise-grade AI models** like OpenAI’s business plan, which does **not** train on company data.
2. **Limit AI Access Using API Authentication**\
   Treat AI like any other third-party software and only grant access to **specific functions the AI needs to perform its tasks**.
3. **Train & Test AI Agents Before Deployment**\
   Use a platform like **Raia** to properly **train, test, and set guardrails** before allowing AI Agents to operate autonomously.
4. **Manage AI Access Control at the Agent Level**\
   If your company is using multiple AI Agents, use **Raia or a similar management platform** to ensure only authorized users can **train, modify, or update agents**.
5. **Encrypt Proprietary Data for AI Training**\
   If you are using AI to process sensitive documents, ensure data is **encrypted in the vector store** before being referenced by AI.
6. **Monitor & Log AI Activity**\
   Set up **audit trails** to track what AI Agents are doing and require **human oversight for critical actions**.
7. **Educate Employees on AI Security Risks**\
   Train employees on **AI phishing risks**, responsible AI usage, and how to verify AI-generated content.
8. **Limit AI Memory & Persistent Storage**\
   Ensure that AI-powered applications **do not store sensitive data beyond what is necessary for a given session**.

#### **Final Thoughts**

AI security isn’t about **fearing AI—it’s about deploying it responsibly**.

The good news is that AI security is **not all that different** from securing traditional software applications. The key is to **understand where the risks are**, set up the right **controls and guardrails**, and **use enterprise-grade AI solutions** that offer better security protections.

By following best practices, businesses can safely integrate AI into their workflows **without exposing sensitive data or creating unnecessary risks**.

In the next lesson, we’ll explore **how to properly train and monitor AI Agents to ensure they stay aligned with business goals**.