Over the past three years, the rise of large language models (LLMs) has transformed the way organizations handle data. AI has become the backbone of productivity—from proposal generation to customer support and internal knowledge sharing.

But with this shift, the concept of data privacy has been rewritten. No longer can companies isolate sensitive information within internal systems. Collaboration and speed now require safe data movement between AI tools and corporate infrastructure. In 2025, sending data through GenAI is table stakes for competitiveness. Refusing to do so often means falling behind in innovation and delivery.

Yet ungoverned use of GenAI creates new attack surfaces. According to IBM’s 2025 Data Breach Report, 13% of organizations reported breaches involving AI models or applications (IBM, 2025). Of those, 97% lacked AI-specific access controls. The message is clear: it’s not AI that causes breaches—it’s a lack of structure.

Balancing Access and Security

AI access shouldn’t be an open door, but it also can’t be locked shut. The goal is to create a governed access model: giving employees AI-powered efficiency while ensuring data never leaves the organization’s control.
Key components of a secure AI usage model include:

1. Limit Public Access to General Chat Tools
   Public interfaces like ChatGPT or Gemini make it easy for sensitive context to leak. Limit or block these in corporate environments.
   Instead, use enterprise-grade AI providers such as Azure OpenAI, Anthropic’s Claude for Enterprise, or askSage: tools that guarantee data isolation, encryption, and compliance visibility.

2. Centralize AI Access Through Secure Platforms
   Deploy AI through managed channels. Integrate LLMs into internal systems or approved SaaS tools with access logs, single sign-on, and usage tracking.
   For example, Settle customers have GenAI embedded directly into their RFP workflows. Proposal data never leaves the platform, yet teams gain all the benefits of automation.

3. Adopt Role-Based AI Permissions
   Not everyone needs access to every model or dataset. Define clear AI roles:

   • Viewers: can query approved data.

   • Editors: can feed content for refinement.

   • Admins: manage data governance and integrations.

   Structured permissions prevent inadvertent exposure while maintaining usability.

4. Establish a Company AI Policy
   A lightweight but explicit policy clarifies what data can be shared with AI tools and under what conditions. Cover:

   • Data classification and handling rules

   • Approved platforms and accounts

   • Logging and retention expectations

   • Review cadence (quarterly or biannually)

   Regular training ensures employees understand both the benefits and boundaries of AI use.

Why This Matters for Revenue Teams

For sales, proposal, and customer success teams, data discipline directly impacts deal velocity and trust. A misplaced piece of proprietary information in a public AI model can cost more than just reputation—it can jeopardize competitive advantage.

Teams that adopt structured, secure AI practices gain measurable advantages:

• Faster RFP turnaround times without compliance risk

• Reduced IT overhead from fewer shadow AI tools

• Improved customer confidence through provable data control

As Settle’s own mission emphasizes, empowering teams to share knowledge efficiently only works if that knowledge remains protected.

The Future of Secure AI Collaboration

AI security is not a one-time investment. As models evolve and data pipelines expand, governance must scale with them. The next phase of enterprise AI will focus on federated knowledge sharing where teams can collaborate through AI without ever exposing raw data externally.

Organizations that get this right won’t have to choose between security and speed. They’ll have both.

References

1. IBM. Cost of a Data Breach Report 2025. https://www.ibm.com/reports/data-breach

2. Microsoft Azure. Enterprise AI Security Overview. https://azure.microsoft.com

3. Settle Vision & Strategy, 2025. Internal Document.

4. askSage. Secure AI for Enterprises. https://asksage.ai