The Non-Negotiable Rules for Safely Using ChatGPT and Generative AI in Your Business
In recent years, generative AI tools like ChatGPT have rapidly gained adoption among both individuals and businesses. Within organizations, teams are leveraging these tools for a wide range of tasks, including drafting emails, brainstorming ideas, writing code, analyzing data, summarizing reports, and even creating media such as videos and images.
With a wide range of use cases, the ability of these tools to help boost productivity is undeniable. However, as businesses rush to adopt these powerful technologies, they often overlook other critical issues, such as data privacy and security. For instance, where does your sensitive data go once you paste it into a chatbot? Who owns the output? What are the legal implications? To leverage AI effectively while staying compliant, businesses must create and enforce clear AI usage policies that protect both the security and privacy of their data.
Why Is This Necessary?
The main risk with generative AI models lies in how they work and how that affects data privacy and confidentiality. For instance, if an employee uploads a confidential client contract into ChatGPT for summarization, the data is posted to a third-party server where it may be stored, reviewed by human trainers, or used to further train the model.
The above scenario alone could constitute a data breach that violates data privacy regulations such as GDPR and HIPAA. Also, AI tools can sometimes produce biased, inaccurate, or copyright-infringing content. Relying on this output without careful review can result in poor decisions, legal risks, and damage to your organization’s reputation. Establishing clear rules for AI use helps ensure innovation remains both safe and responsible.
Rule 1. Govern Your Data With a Clear AI Policy
The key principle for using generative AI tools is controlling the data you share. This requires a formal AI use policy that clearly outlines what types of information should never be entered into third-party or public AI models. At a minimum, the policy should cover:
- Customer and employee personal information (PII)
- Sensitive financial data and internal business reports
- Trade secrets and intellectual property, such as schematics, design documents, or source code
- Privileged or legally protected communications
This policy should be formally communicated to every employee and incorporated into both onboarding and ongoing security training. To reduce shadow IT risks, consider approving specific, vetted AI tools for business use and restricting access to unapproved public AI platforms through network-level content filtering.
Rule 2. Validate AI Output, Never Trust It
When working with generative AI, always operate on the premise that AI-generated content is unverified draft material. This idea is based on a well-documented flaw known as “AI hallucinations,” where models generate plausible but entirely false output. This means putting mandatory human review in place for any AI-generated content used in official communications, financial reporting, legal documents, or customer-facing materials. Employees should be trained to fact-check sources, validate calculations, and apply critical judgment.
There is also a significant risk of plagiarism or copyright violations, since AI models are trained on large datasets that may contain copyrighted material such as books and images. Because ownership of AI-generated content remains a gray area, it’s best practice to disclose AI use when appropriate and thoroughly review the final output to ensure it’s original and does not infringe on others’ intellectual property.
Rule 3. Train Your Teams and Assign Accountability
Technology policies only work when employees understand and follow them. Train your team on your secure AI guidelines, explain the reasoning behind each rule, and use real examples of data leaks or incidents caused by improper AI use. Encourage questions and offer clear channels for employees to get guidance when they’re unsure.
Finally, assign clear accountability by designating individuals or teams to own the AI usage policy, monitor emerging risks, and update guidelines as technology and the regulatory landscape evolve. This means staying informed through resources such as the NIST AI Risk Management Framework (AI RMF).
Ultimately, these rules give your organization a confident, structured way to use AI. They enable teams to explore generative AI’s benefits within safe boundaries that protect your data and reputation, shifting AI use from risky experimentation to strategic, controlled adoption.
Ready to build a safe and effective AI strategy for your business? Reach out to Sound Computers for a consultation, and we’ll help you come up with a secure AI use policy, implement technical safeguards, and even train your teams to navigate this new frontier confidently.
Article FAQ.
Is it safe to enter customer information into ChatGPT?
No. Customer personally identifiable information (PII) is confidential and protected by regulations such as HIPAA and GDPR. Entering it into third-party AI tools such as ChatGPT risks a data breach and compliance violations.
Who owns the content created by AI tools such as ChatGPT?
Currently, the ownership of AI-generated content remains a contentious and evolving legal issue that is not clearly defined. To ensure ownership, businesses should treat AI output as draft content that needs significant human review and finalization to ensure it is a new and original work output.
What are AI hallucinations?
AI hallucinations occur when generative AI tools provide factually incorrect or nonsensical output confidently and persuasively. Examples include fake citations and historical events, wrong calculations, and fake statistics. All AI output needs human fact-checking and verification.
Can businesses just block all AI tools at work to stay safe?
Blocking every AI tool might seem like the safest option, but it’s not a practical long-term strategy. It can slow productivity, especially when competitors are already benefiting from AI, and it often drives employees to use unapproved tools, creating even more risk. A better approach is to implement a clear AI policy, provide training, and offer vetted, secure AI tools for employees to use.
What is the first step in creating an AI policy for my company?
Start by bringing together key stakeholders, IT, security, legal, and department leaders, to understand how AI is currently being used and where teams want to adopt it. From there, draft a policy tailored to your organization’s data and risk tolerance, beginning with clear, strict rules about what information can and cannot be entered into AI tools.
