Public vs Private LLMs: Security, Governance and Architecture Considerations
AI adoption is accelerating across organisations. But one of the most important decisions often gets overlooked: should we use public AI models or private LLMs? This is not just a technical choice. It is a security, governance, and risk decision.
28 Apr 2026
~9 min read
Saleem Yousaf
Public LLMs: Fast, Scalable, Accessible
Public AI platforms such as ChatGPT, Copilot, and Gemini offer rapid deployment, high capability, and low barrier to entry. They are ideal for general productivity, content generation, and non-sensitive workloads. However, public LLMs introduce challenges: limited control over data processing, potential data retention and reuse, and reduced visibility and auditability.
Private LLMs: Controlled, Secure, Customised
Private LLMs hosted in controlled environments offer full control over data, enhanced security and privacy, integration with internal systems, and customisation for business use. The trade-offs are higher cost, operational complexity, and maintenance overhead. Private models are the right choice when data sensitivity, regulatory obligations, or business criticality require it.
Governance Is the Deciding Factor
The real decision is not public versus private. It is what level of control is required for the data and use case. Factors include data classification and sensitivity, regulatory obligations, business criticality, user base and access requirements, and cost versus control trade-offs.
The Hybrid Model: Best Practice
Most organisations will adopt a hybrid approach. Public AI for low-risk, general tasks and non-sensitive workloads. Private LLM for sensitive data, critical workflows, regulated data, and proprietary business processes. The key is having a clear policy that defines which model tier applies to which data and use case.
Data classification before any AI usage
Identity and access control for AI services
Monitoring and logging of all AI interactions
Clear AI acceptable use policies
Data residency and sovereignty requirements
Vendor security assessment before procurement
The organisations that succeed will not be the fastest adopters. They will be the ones that adopt AI with governance at the core.
// Public vs private LLM security and governance considerations