AI Security Awareness: Emerging Risks and How to Use AI Safely at Work

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This security awareness training covers common AI tools, AI-related security risks, shadow AI, data exposure, hallucinations, AI-enhanced phishing and deepfakes, tool vetting, secure data handling, and the importance of human review.

The Short Answer

AI can help employees write, summarize, research, analyze, automate, code, and complete routine work more efficiently. But AI tools also introduce new security risks when employees share sensitive information, use unapproved tools, trust inaccurate outputs, or assume AI-generated content is legitimate.

Attackers are also using AI to make phishing, impersonation, deepfakes, voice cloning, reconnaissance, and other social-engineering attacks more convincing.

Safe AI use requires clear policies, approved tools, appropriate data handling, employee awareness, tool vetting, and human review of AI-generated outputs.

AI Security Awareness at a Glance

• Do not put sensitive information into unapproved AI tools. Treat prompts, uploads, documents, code, and other inputs as data being shared with another system.
• AI can be wrong. Confident-sounding output is not the same as accurate output.
• Watch for shadow AI. Employees should not introduce new AI tools into company workflows without appropriate review.
• AI makes social engineering more convincing. Perfect grammar, realistic voices, personalized messages, and believable video are no longer proof that a request is legitimate.
• Use approved tools and follow company policy. Different AI platforms may have different privacy, retention, access, and security practices.
• Keep a human in the loop. AI should support critical thinking, not replace it.

What Is AI Security Awareness?

AI security awareness means understanding how the use of artificial intelligence can affect data, privacy, cybersecurity, decision-making, and everyday employee behavior.

AI is increasingly built into email, productivity software, search, customer-service platforms, development tools, collaboration systems, and other applications employees may already use.

That means AI security is no longer only a concern for technical teams. Anyone using AI as part of their work can influence the organization's risk.

What Are the Biggest Security Risks of AI?

The training highlights several common risks employees should understand.

Data Exposure

Employees may unintentionally expose confidential information by entering sensitive data, internal documents, customer information, proprietary code, or other protected material into an AI platform.

AI Hallucinations

AI systems can generate inaccurate, misleading, or fabricated information while presenting it confidently. Users who treat those responses as verified facts can introduce errors into business decisions and work products.

Shadow AI

Shadow AI occurs when employees use AI tools without organizational approval or oversight. Those tools may not meet company expectations for privacy, security, data retention, compliance, or access control.

Overreliance

AI can accelerate work, but employees should not allow it to replace critical thinking. Decisions still require appropriate human judgment, especially when security, legal, financial, customer, or business consequences are involved.

Loss of Attribution

AI-generated answers may make it difficult to determine where information originated. That can complicate source verification, accuracy checks, and accountability when incorrect information is repeated.

What Is Shadow AI?

Shadow AI is the use of artificial-intelligence tools outside the organization's approved technology and governance processes.

An employee might discover a useful AI website, browser extension, coding assistant, chatbot, transcription service, or productivity application and begin using it without realizing that the tool is processing company information.

The problem is not simply that the tool is new. The organization may have no visibility into:

• What information employees are entering
• Where that information is stored
• How long it is retained
• Whether prompts or uploads are reused
• Which security controls protect the platform
• Whether the tool complies with company policies and requirements

Organizations need practical AI governance that gives employees clear guidance about which tools are approved and how they can be used.

What Information Should You Avoid Putting Into AI?

Employees should follow their organization's data-classification rules and AI policies before entering information into an AI system.

Information that may require additional protection includes:

• Customer information
• Employee personal information
• Passwords, credentials, keys, or secrets
• Confidential business documents
• Proprietary source code
• Financial or strategic information
• Protected or regulated data
• Any information the organization does not permit employees to share with the selected AI provider

When in doubt, employees should stop and verify whether the tool and the intended use are approved before submitting the information.

Why Should You Verify AI-Generated Information?

AI systems generate responses based on patterns in information rather than independently verifying every statement before producing an answer.

An answer can therefore sound polished, specific, and authoritative while still being incomplete or wrong.

Employees should review important outputs, verify sources when necessary, apply their own expertise, and remain accountable for the work they ultimately use or submit.

How Is AI Changing Phishing?

Traditional phishing advice often told users to look for poor grammar, strange wording, misspelled company names, or obviously generic messages.

AI makes those warning signs less reliable.

Attackers can generate polished messages quickly and personalize them using publicly available information about an employee, executive, customer, company, or recent event.

Employees therefore need to evaluate the request itself — not simply whether the email looks professionally written.

How Do Deepfakes and Voice Cloning Affect Security Awareness?

AI can be used to imitate a person's voice, appearance, or communication style.

That means a voicemail, video call, voice message, or other communication that appears to come from an executive or coworker should not automatically be trusted when the request itself is unusual.

Requests involving urgent payments, credentials, system access, confidential information, account changes, or unusual exceptions should be verified using a trusted communication channel.

Can an AI Tool Itself Be Malicious?

Yes. Employees should not assume that every website or application claiming to provide AI functionality is legitimate.

A malicious or compromised AI service could collect information submitted by users, return harmful code, direct users toward malicious content, or otherwise create a security problem.

That is why organizations should vet AI tools before employees begin using them with company information or connecting them to company systems.

How Can Employees Recognize AI-Enhanced Social Engineering?

AI allows attackers to gather public information and create more personalized social-engineering attempts.

Instead of focusing only on grammar or appearance, employees should look for behavioral warning signs such as:

• Unexpected urgency
• Requests to bypass normal procedures
• Unusual payment instructions
• Requests for credentials or sensitive information
• Unexpected access requests
• Pressure to keep the request secret
• Communication that seems plausible but is inconsistent with the person's normal behavior

When the request is unusual, verify it independently before acting.

Safe AI Use Checklist

1. Follow company policy. Know which AI tools and use cases are approved.
2. Use approved AI tools. Do not introduce unknown AI platforms into business workflows without review.
3. Protect sensitive data. Do not upload confidential or protected information unless the organization has explicitly approved that use.
4. Think before you prompt. Consider what information you are providing to the AI system.
5. Verify outputs. Check important facts, sources, calculations, recommendations, and conclusions.
6. Watch for AI-enhanced phishing. Professional writing, familiar voices, and convincing video are not proof of identity.
7. Verify unusual requests. Use a trusted second channel when money, access, credentials, or sensitive information are involved.
8. Keep humans accountable. AI can assist the work, but people remain responsible for the outcome.
9. Ask when unsure. Contact the appropriate security, IT, privacy, or management resource before using an unfamiliar AI tool for company business.

Why Do Organizations Need AI Policies?

Employees cannot consistently make good AI risk decisions if the organization has never explained what good AI use looks like.

Policies and guidance can define:

• Approved AI platforms
• Permitted business uses
• Prohibited information and data types
• Required human review
• Tool-review and approval processes
• Security and privacy requirements
• How employees should report concerns or questions

The objective is not simply to restrict AI. Good governance helps organizations use AI intentionally while reducing unmanaged risk.

Frequently Asked Questions

What Is AI Security Awareness?

AI security awareness helps employees understand the cybersecurity, privacy, data, accuracy, and social-engineering risks associated with AI and how to use AI tools more safely.

What Is Shadow AI?

Shadow AI is the use of AI tools without appropriate organizational approval or oversight. It can create blind spots involving sensitive data, privacy, security, compliance, retention, and vendor risk.

Can Employees Put Company Information Into ChatGPT or Other AI Tools?

Employees should follow their organization's policies and use only approved tools and approved data. Sensitive, confidential, regulated, or proprietary information should not be submitted to an AI service unless the organization has determined that the use is appropriate.

What Is an AI Hallucination?

An AI hallucination is inaccurate or fabricated information generated by an AI system. Because the response may sound confident, users should verify important outputs rather than assuming they are correct.

How Does AI Make Phishing More Dangerous?

AI can help attackers quickly create polished, personalized messages using public information. That makes traditional warning signs such as spelling and grammar mistakes less reliable.

Can AI Be Used for Deepfake Scams?

Yes. AI can be used to imitate voices and appearances, making fraudulent requests seem more believable. Employees should independently verify unusual requests involving money, credentials, access, or confidential information.

Should AI Replace Human Review?

No. AI can assist employees, but important outputs should still be reviewed by a person who can evaluate accuracy, context, risk, and whether the result is appropriate for the intended use.

About This Security Awareness Training

This article is based on a Hotman Group security awareness training focused on artificial intelligence and emerging security risks.

The training focuses on practical awareness and secure AI behavior rather than technical AI implementation, including data exposure, hallucinations, shadow AI, overreliance, phishing, deepfakes, malicious AI tools, tool vetting, data controls, and human oversight.

Using AI Without Creating Unmanaged Risk

AI is becoming part of everyday business operations. The goal does not need to be avoiding AI — it is understanding where risk enters the process and putting appropriate governance, security practices, and human oversight around its use.

Hotman Group is a cybersecurity and Cyber GRC professional-services firm that helps organizations diagnose, design, build, remediate, implement, operate and mature cybersecurity programs.

HG helps organizations connect AI governance to broader cybersecurity risk, data protection, policies, controls, third-party oversight, and business strategy rather than treating AI as a separate compliance exercise.

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