6 Essential Strategies for Safe AI Use
Artificial intelligence has transformed how businesses operate, from drafting emails in seconds to summarizing complex reports with ease. Public AI tools like ChatGPT and Gemini have become indispensable for brainstorming ideas, writing marketing copy, and streamlining everyday workflows. However, for businesses handling sensitive customer information, these powerful tools come with serious security risks that can’t be ignored.
The reality is stark: most public AI tools use the data you provide to train and improve their models. Every prompt entered could potentially become part of their training data. A single employee mistake could expose client Personally Identifiable Information (PII), internal strategies, or proprietary processes. As business leaders, preventing data leakage before it becomes a serious liability must be a top priority.
The True Cost of Data Exposure
Integrating AI into your business workflows is essential for staying competitive, but doing it safely is non-negotiable. The cost of a data leak resulting from careless AI use far outweighs the cost of preventative measures. When sensitive information is exposed, the consequences can be devastating: regulatory fines, loss of competitive advantage, and long-term damage to your company’s reputation.
Consider Samsung’s 2023 incident as a cautionary tale. Multiple employees in the company’s semiconductor division, seeking efficiency gains, accidentally leaked confidential data by pasting it into ChatGPT. The leaks included source code for new semiconductors and confidential meeting recordings, which were then retained by the public AI model for training. This wasn’t a sophisticated cyberattack—it was human error resulting from a lack of clear policy and technical guardrails. Samsung’s response? A company-wide ban on generative AI tools to prevent future breaches.
6 Prevention Strategies for Secure AI Use
Here are six practical strategies to secure your interactions with AI tools and build a culture of security awareness within your organization.
1. Establish a Clear AI Security Policy
When it comes to data security, guesswork won’t cut it. Your first line of defense is a formal policy that clearly outlines how public AI tools should be used. This policy must define what counts as confidential information and specify which data should never be entered into a public AI model—social security numbers, financial records, merger discussions, product roadmaps, and customer PII.
Educate your team on this policy during onboarding and reinforce it with quarterly refresher sessions to ensure everyone understands the serious consequences of non-compliance. A clear policy removes ambiguity and establishes firm security standards across your organization.
2. Mandate the Use of Dedicated Business Accounts
Free, public AI tools often include hidden data-handling terms because their primary goal is improving the model. Upgrading to business tiers such as ChatGPT Team or Enterprise, Google Workspace with Gemini, or Microsoft Copilot for Microsoft 365 is essential. These commercial agreements explicitly state that customer data is not used to train models. By contrast, free or Plus versions of ChatGPT use customer data for model training by default, though users can adjust settings to limit this.
The data privacy guarantees provided by commercial AI vendors establish a critical technical and legal barrier between your sensitive information and the open internet. With these business-tier agreements, you’re not just purchasing features—you’re securing robust AI privacy and compliance assurances from the vendor.
3. Implement Data Loss Prevention Solutions with AI Prompt Protection
Human error and intentional misuse are inevitable realities. An employee might accidentally paste confidential information into a public AI chat or attempt to upload a document containing sensitive client data. You can prevent this by implementing Data Loss Prevention (DLP) solutions that stop data leakage at the source. Tools like Cloudflare DLP and Microsoft Purview offer advanced browser-level context analysis, scanning prompts and file uploads in real time before they ever reach the AI platform.
These DLP solutions automatically block data flagged as sensitive or confidential. For unclassified data, they use contextual analysis to redact information that matches predefined patterns, like credit card numbers, project code names, or internal file paths. Together, these safeguards create a safety net that detects, logs, and reports errors before they escalate into serious data breaches.
4. Conduct Continuous Employee Training
Even the most comprehensive AI use policy is ineffective if it simply sits in a shared folder collecting digital dust. Security is a living practice that evolves as threats advance, and basic compliance lectures are never enough.
Conduct interactive workshops where employees practice crafting safe and effective prompts using real-world scenarios from their daily tasks. This hands-on training teaches them to de-identify sensitive data before analysis, turning staff into active participants in data security while still leveraging AI for efficiency gains.
5. Conduct Regular Audits of AI Tool Usage and Logs
Any security program only works if it’s actively monitored. You need clear visibility into how your teams are using public AI tools. Business-grade tiers provide admin dashboards—make it a habit to review these weekly or monthly. Watch for unusual activity, patterns, or alerts that could signal potential policy violations before they become a problem.
Audits are never about assigning blame. They’re about identifying gaps in training or weaknesses in your technology stack. Reviewing logs might help you discover which team or department needs extra guidance or indicate areas where you need to refine your approach and close loopholes.
6. Cultivate a Culture of Security Mindfulness
Even the best policies and technical controls can fail without a culture that supports them. Business leaders must lead by example, promoting secure AI practices and encouraging employees to ask questions without fear of reprimand.
This cultural shift turns security into everyone’s responsibility, creating collective vigilance that outperforms any single tool or policy. When every team member understands their role in protecting company data, your people become your strongest line of defense.
Make AI Safety a Core Business Practice
Integrating AI into your business workflows is no longer optional—it’s essential for staying competitive and boosting efficiency. That makes doing it safely and responsibly your top priority. The six strategies we’ve outlined provide a strong foundation to harness AI’s potential while protecting your most valuable asset: your data.
Don’t wait for a data breach to take action. FSET’s cybersecurity experts can help you develop and implement comprehensive AI security policies tailored to your business needs. As an ISO 27001-certified managed service provider, we specialize in protecting sensitive data for organizations across law enforcement, healthcare, and other specialized industries.
Ready to secure your AI adoption strategy? Contact FSET today to discuss how we can help safeguard your business.
