The allure of "turnkey" AI solutions is strong.
It is faster to deploy, easier to manage, and looks great in a quarterly update.
But speed today often creates paralysis tomorrow.
In my time advising boards on digital transformation, I have seen the same pattern repeat.
An organization adopts a proprietary ecosystem for convenience, only to find themselves trapped when pricing spikes or performance plateaus.
The problem is compounded with AI.
If your data is formatted exclusively for one vendor's proprietary model, or if your agents are built on a closed logic layer, you aren't just using a tool.
You are outsourcing your intellectual property and operational agility.
A board that doesn't audit for lock-in is not managing risk; they are ignoring it.
The goal isn't to avoid big vendors, but to ensure the cost of exiting is not catastrophic.
The Executive and Board’s Due Diligence Checklist:
1. Model Portability
Can we move our prompts and fine-tuning data to a different LLM without starting from scratch?
2. Data Sovereignty
Do we own the outputs and the refined weights, or does the vendor?
3. Integration Layer
Are we building directly into a proprietary API or using an abstraction layer that allows us to swap models?
4. Exit Strategy
What is the documented, costed plan for migrating to a competitor in 24 months?
Is your AI strategy built for agility, or are you just renting your intelligence from someone else?
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