Public AI data security is now a real and growing risk for modern businesses. Teams use public AI tools every day to brainstorm ideas, draft emails, write marketing content and summarise reports. Used correctly, these tools improve productivity and save time.
The risk appears when sensitive information is entered into public AI platforms without safeguards.
Many public AI tools may store, or process prompts to improve their models, depending on platform settings and terms of use. A single careless prompt can expose customer personally identifiable information (PII), internal strategies or proprietary business data. For this reason, organisations must address public AI data security clearly and early.
Financial and Reputational Risks of Poor Public AI Data Security
Unsafe AI use can lead to serious consequences. Data breaches often result in regulatory penalties, legal costs and long-term loss of customer trust. In many cases, recovery costs far exceed prevention costs.
Samsung’s 2023 ChatGPT incident is a timely reminder: some of the biggest security risks don’t come from attackers, they come from everyday behaviours. In this case, staff reportedly pasted confidential semiconductor source code into ChatGPT, creating an internal data exposure. It wasn’t a cyberattack, but it did highlight the need for clear AI usage policies, staff training, and technical controls. Samsung later restricted generative AI tools across the organisation as part of its response.
This example shows that public AI data security failures usually result from governance and process gaps, not technical complexity.
Six Practical Ways to Improve Public AI Data Security
1. Create a Clear AI Security Policy
Every business should document how staff can and cannot use public AI tools. A strong AI policy clearly defines which data staff must never enter into AI platforms, including customer PII, financial data, legal matters, internal code and product roadmaps.
Businesses should include this policy in onboarding and reinforce it regularly. Clear guidance removes ambiguity and reduces accidental exposure.
2. Use Business-Grade AI Accounts
Free AI tools may use submitted data for model training. Business-grade platforms such as ChatGPT Enterprise, Microsoft Copilot for Microsoft 365, and Google Workspace AI provide stronger data protection commitments.
Businesses should mandate approved commercial AI accounts and restrict access to unapproved tools for work-related use.
3. Implement Data Loss Prevention for AI Prompts
Policies alone are not enough. Technical controls provide an additional layer of protection.
Data loss prevention (DLP) tools such as Microsoft Purview and Cloudflare DLP can scan AI prompts and file uploads in real time. These tools detect sensitive data and block or redact it before submission, preventing small mistakes from becoming serious incidents.
If you want to reduce AI-related risk and protect sensitive data across your environment, our cybersecurity services can help implement the right controls.
4. Train Staff to Use AI Safely
Even strong controls fail if staff do not understand safe AI use. Training should focus on recognising risky prompts, anonymising data correctly and understanding when AI should not be used at all.
Ongoing education is essential as AI tools, features and risks continue to change.
5. Review AI Usage and Logs Regularly
Business AI platforms provide usage logs and admin dashboards that offer visibility into how AI tools are being used.
Regular reviews help identify unusual behaviour, training gaps or policy weaknesses early. These reviews should focus on improving processes, not assigning blame.
6. Build a Culture of Security Awareness
Public AI data security ultimately depends on culture. When leaders model responsible AI use and encourage questions, staff are more likely to make secure decisions.
A strong security culture consistently reduces risk more effectively than technology alone.
Make Public AI Data Security a Core Business Practice
AI is now a standard part of business operations. Avoiding it entirely is unrealistic but using it without safeguards creates unnecessary risk.
When clear AI policies, business-grade tools, staff training and technical controls work together, organisations can confidently adopt public AI tools while maintaining secure and compliant environments. Managed IT services play a key role by overseeing security controls, compliance and ongoing risk management.
If you need help implementing practical and secure AI safeguards, Contact our team to discuss how we can support your business.
