Private AI vs Public AI
Is the Difference Just About Where It's Deployed — or Who Actually Controls the Data?
More organizations are adopting AI seriously than ever before. Whether it is used for research, problem-solving, or creating new solutions such as agentic coding, the conversation quickly changes once AI begins interacting with real business data.
The question IT teams are hearing more frequently is no longer:
"Is the AI smart enough?"
Instead, it becomes:
How can we use AI while keeping our organization's sensitive information secure?
Where is the data being sent?
Who has access to it?
And does the organization still maintain full control?
At first, Public AI appears to be the easiest option. Simply open a website, sign up, and start using it immediately. The entire team can gain access within minutes.
However, once organizations begin using AI with internal documents, customer information, or proprietary business knowledge, many companies start realizing that convenience may come with hidden risks, such as:
Internal documents being submitted to public AI platforms without clear governance controls
Different teams adopting different AI tools without centralized oversight or cost management
AI-generated answers that sound convincing but cannot be verified (AI Hallucination)
Uncertainty about whether sensitive information could unintentionally leave the organization
These concerns have led many organizations to clearly separate Public AI from Private AI.
The fundamental distinction is simple.
Public AI is designed to work with publicly available information and general knowledge.
Private AI, on the other hand, is designed to work with organization-specific information, including internal documents stored in SharePoint, ERP systems, Excel spreadsheets, ticketing systems, and other enterprise platforms. Everything remains under the organization's existing infrastructure and security policies.
The real difference is not how the AI looks.
The difference lies in the level of control an organization has over its data and workflows.
The question is no longer:
"Should we use AI?"
Most organizations already are.
The real question is:
"How can we use AI while ensuring our data remains under our control?"
This is the challenge Throughwave helps organizations solve—from designing Private AI environments on their own infrastructure, connecting with existing systems such as SharePoint, ERP, and internal applications, to implementing governance frameworks that allow teams to use AI efficiently while giving IT full visibility and control.
If your organization is beginning to take AI seriously and wants to ensure that critical information remains protected, we would be happy to discuss and evaluate the most suitable approach for your environment.
Public AI vs Private AI
Many people assume that Private AI simply means deploying a ChatGPT-like solution inside the company. In most cases, this involves running an open-source Large Language Model (LLM) on the organization's own infrastructure.
However, the real challenge is not the model itself.
The more important challenge is enabling AI to understand the organization's actual knowledge and the relationships between different pieces of information.
In reality, information is rarely stored in one place.
Some data resides in SharePoint.
Some remains in old Excel files.
Some exists inside ticketing systems.
And sometimes the most valuable knowledge still lives in the minds of experienced employees.
That is why many organizations do not suffer from a lack of information.
They suffer from an inability to find the information they already have.
Employees repeatedly ask the same people for answers
Teams open multiple systems to find a single piece of information
Staff search through numerous files before locating what they need
Valuable time is spent searching before actual work can begin
This is one of the primary reasons organizations are moving beyond general-purpose AI toward Private RAG AI solutions.
Private RAG AI continuously crawls and connects information across multiple systems, allowing AI to access the latest information and respond with a much deeper understanding of the organization's actual context.
The results are often visible across multiple departments:
IT teams reduce repetitive support tickets
HR teams spend less time answering recurring policy questions
Support teams respond to customers faster
Employees gain access to organizational knowledge from a single location
Most importantly, AI is no longer "guessing."
It is responding based on the organization's real information.
For many IT Managers, the real turning point is not that AI becomes smarter.
It is that AI becomes practical for business use while maintaining governance, security, and operational control.
Ultimately, there is no universal answer to whether Public AI or Private AI is the better choice.
However, once AI begins interacting with sensitive organizational information, issues such as Security, Compliance, and Data Ownership become impossible to ignore.
Because AI that truly delivers value inside an organization is not simply AI that generates impressive answers.
It is AI that allows the IT team to confidently say:
"Our data remains fully under our control."
For organizations that want to use AI confidently with internal information, Throughwave helps design and implement Private AI and Private RAG solutions running on your own infrastructure, connected to your existing knowledge sources and business systems, with governance and auditability built into every step.
Interested in exploring Private AI for your organization?
Contact the Throughwave team today.