Stop Renting Intelligence: Why Enterprise AI Is Headed in the Wrong Direction
- 6 days ago
- 4 min read
Last week, Palantir CEO Alex Karp delivered a message that many enterprise leaders have been thinking privately for months:
"Something has gone completely wrong with how AI is sold."
His criticism wasn't about AI itself. It was about the business model emerging around it. According to Karp, enterprises are being encouraged to consume more and more tokens while receiving questionable long-term value in return. More importantly, many organizations are unknowingly transferring their most valuable asset—their intellectual property and know-how—into systems they do not control. [cnbc.com], [https://ww...-sold.html]
Whether you agree with Karp's conclusions or not, his comments raise a fundamental question:
What are enterprises actually buying when they buy AI?
And perhaps more importantly:
What are they giving away?
The Great Enterprise AI Illusion
Most AI vendors want you to believe that the model is the product.
It isn't.
The model is merely the engine.
The real value comes from the information flowing into it.
Every day, professionals interact with AI systems and provide:
Business strategies
Client information
Work product
Research methodologies
Operating procedures
Pricing models
Billing practices
Internal know-how
The more useful AI becomes, the more proprietary knowledge organizations feed into it.
In legal services, this problem is even more pronounced.
A billing narrative isn't merely a billing narrative.
It contains decades of expertise:
How a firm staffs matters
How attorneys describe legal work
How client guidelines are interpreted
How matters are categorized
How write-offs are avoided
How profitability is maximized
This is not data.
This is competitive advantage.
Yet many firms are sending this information through third-party AI platforms every single day.
And then paying for the privilege.
The Hidden Cost of Token-Based AI
The discussion around AI usually focuses on token costs.
How many tokens were consumed?
How much did the request cost?
How can usage be reduced?
These are the wrong questions.
The real cost is not the tokens.
The real cost is the gradual transfer of institutional knowledge outside the organization.
Every prompt teaches something.
Every correction teaches something.
Every approved billing entry teaches something.
Every user interaction contains context that reflects how your organization operates.
Over months and years, this becomes one of the most valuable datasets your firm possesses.
Unfortunately, many organizations spend enormous effort protecting document repositories, financial systems, and confidential matter data while simultaneously allowing AI interactions to become the largest uncontrolled knowledge extraction mechanism in the business.
The irony is painful:
Companies spend millions protecting intellectual property while feeding it into systems they don't own.
AI Models Are Becoming Commodities
Another uncomfortable truth is that today's leading model may not be tomorrow's leading model.
The AI industry moves too quickly.
The model that dominates today may be replaced six months from now.
Changing LLM providers should not require rebuilding your business.
Yet many organizations are allowing their AI strategy to become tightly coupled to a particular vendor.
That creates dependency.
It creates lock-in.
And ultimately it weakens negotiating power.
Enterprise value does not reside in the model.
Enterprise value resides in:
Your data
Your workflows
Your expertise
Your governance
Your proprietary knowledge
The model is replaceable.
Your firm's accumulated know-how is not.
The Difference Between an LLM and Your LLM
This is where many AI discussions become dangerously simplistic.
People often assume that deploying AI means sending requests to a third-party model provider.
That is only one possible architecture.
At Matteroom, we believe there should be a clear separation between:
The foundation model.
Your firm's proprietary intelligence.
The foundation model provides general language, reasoning, and inference capability.
Your firm's intelligence is something entirely different.
Your billing practices.
Your matter classifications.
Your OCG interpretations.
Your preferred narrative styles.
Your specialized terminology.
Your institutional knowledge.
These represent years or decades of accumulated expertise.
They should not become part of someone else's business model.
How MIRA+ Approaches AI Sovereignty
This philosophy is one of the reasons MIRA+ supports a Bring Your Own LLM (BYO-LLM) model. Internally, Matteroom has described this approach as allowing organizations to use preferred AI models while maintaining ownership of trained data, AI investments, and governance policies. [Marketing Chat Group | Teams], [Steven Wang in chat | Teams]
More importantly, our methodology is designed around a simple principle:
Your custom intelligence should remain separate from the public foundation model.
When customers deploy MIRA+ using their own LLM environment:
The base model remains the base model.
Your firm's customizations remain in your environment.
Your training data remains under your control.
Your governance policies remain your policies.
Your know-how remains your know-how.
The objective is not merely to use AI.
The objective is to ensure that as AI becomes smarter about your business, that intelligence remains an asset owned by your organization.
Think of it this way:
Most AI vendors focus on making the model smarter.
We focus on making your firm smarter.
There is a significant difference.
One approach accumulates value for the AI provider.
The other accumulates value for the customer.
The Future Is Owned Intelligence
Karp's comments resonate because they highlight a shift that many enterprises are already beginning to recognize.
The future of enterprise AI is not simply about model performance.
It is about ownership.
Ownership of:
Data
Models
Policies
Compute
Institutional knowledge
Competitive advantage
Organizations that build AI strategies around sovereignty will retain control over the value they create.
Organizations that do not may eventually discover that they spent years paying token fees while simultaneously helping others understand their business better than they understand it themselves.
That is not digital transformation.
That is outsourced intelligence.
A Simple Question Every CIO Should Ask
Before purchasing another AI platform, ask a simple question:
"When this system becomes deeply knowledgeable about how my business operates, who owns that knowledge?"
If the answer is unclear, you may not be buying AI.
You may be renting intelligence.
And paying to give away your own.
MIRA+ Philosophy
Your Data.Your Know-How.Your LLM.
Because AI should learn from your organization.
Not learn your organization.
