When your team uses generative AI tools like ChatGPT, Claude, or Perplexity, you're not just typing prompts into a box – you're making decisions about how your organization's data is handled. One of the biggest choices you face is whether to allow your data to be used for training large language models (LLMs).
This isn't just a personal preference. For business leaders, it's a governance decision that touches on security, intellectual property, and organizational risk.
What It Means to "Use Data for Training"
When you allow a platform to use your inputs for training, your prompts and outputs may be incorporated into future versions of the AI. This training process can improve the system overall, but it also means:
- Your data leaves your control. Even if anonymized, it becomes part of the model.
- Confidential details may be exposed. Sensitive business information and intellectual property (including new ideas that your team is working on) could unintentionally resurface in unexpected contexts.
- You give up oversight. Once included in training, you can't retract it.
For leaders overseeing organizational knowledge, corporate IP, or regulated data, this should raise red flags.
The Current Defaults (Fall 2025)
- ChatGPT (OpenAI): In paid "Team" or "Enterprise" plans, data is not used for training by default. Admins can enforce this setting for the entire organization.
- Claude (Anthropic): Paid "Pro" and enterprise plans allow you to disable training. With enterprise accounts, settings can be enforced centrally.
- Perplexity: For individual paid accounts, you can adjust privacy settings yourself to restrict training use.
The bottom line: if you're on a free or one-off account, assume your data will be used for training unless you explicitly change settings.
Beyond Training: Other Security Risks Still Apply
Even if you disable training, risks remain:
- Data sharing and access. Your queries may be logged for debugging or abuse detection.
- Accidental oversharing. Staff may paste in sensitive documents without realizing implications.
- Shared links. Many platforms let you generate shareable links to chats or threads. These links sometimes get indexed by search engines, meaning your "private" exchange could show up publicly.
- Connectors and integrations. Adding third-party connectors (e.g., linking your Google Drive, SharePoint Online, CRM, Dropbox, or Slack tenant to an AI platform) can expand the risk surface. A misconfigured connector could expose sensitive data far beyond what you intend.
- Compliance gaps. Industry-specific requirements (HIPAA, GDPR, federal contract rules, etc.) may be impacted.
The choice isn't between "safe" and "unsafe," it's about being intentional, managing risks, setting expectations, and having clear organizational policies.
What This Means for Your Organization
- For Enterprise/Team Accounts: Take advance of centralized controls. Set organizational defaults so staff don't have to decide on an individual basis.
- For One-Off Paid Accounts (like Perplexity Pro): Adjust privacy settings manually in the account dashboard. Train staff to check and confirm settings.
- For All Accounts: Establish clear internal guidance about what data can and cannot be shared with AI tools.
This isn't about saying "don't use AI." It's about using it thoughtfully, balancing productivity with security, protecting intellectual property, and reducing compliance risk.
A Practical Next Step
Business leaders should ask:
- Have we set organization-wide privacy defaults where possible?
- Do we know what kinds of data our teams are putting into these tools?
- Do we have clear policies about AI usage? And are staff trained to follow them?
Intentional use of AI means thinking beyond convenience to long-term security and governance. As with any other technology decision, your mission, intellectual property, and, potentially, your stakeholders' data, deserve protection.
✅ Key takeaway: Paid plans give you more control over whether your data is used for training. But disabling training isn’t the end of the conversation — it’s the beginning of building a thoughtful, security-aware AI policy.
Not Sure Where to Start?
If you’re trying to navigate these questions — privacy settings, connectors, governance policies, and more — you don’t have to do it alone. FireOak can help your leadership team cut through the noise, understand the risks, and put the right safeguards in place.
👉 Let’s talk about how to make AI work for your organization, securely and strategically.
