Do Not Buy an AI Demo: 12 Vendor Questions
Evaluate data use, model portability, service levels, testing, audit, exit and total cost instead of presentation quality.
Start by Clarifying the Operating Impact
AI demos use curated conditions; production contains exceptions. Evaluate vendors on your data, workflows and failure scenarios.
Core decision: A durable vendor discusses limits, failure, responsibility and exit—not only successful demonstrations.
Design Principles
- Test real cases and acceptance sets
- Clarify training use, retention and location
- Plan for model, price and service changes
- Preserve export, migration and termination options
Practical Implementation Steps
- Set business and quality thresholds
- Document data flow and subprocessors
- Test error, refusal and escalation
- Compare build, run, support and exit cost
- Contract monitoring, notification and accountability
Keep baselines, decision rationale and results at every step so the next expansion is based on evidence rather than memory.
Decision Note
A durable vendor discusses limits, failure, responsibility and exit—not only successful demonstrations.
Research and Policy Sources
This guide reorganizes the following official frameworks, policies and research into a practical adoption method.
FAQ
Single platform or multi-model architecture?
A durable vendor discusses limits, failure, responsibility and exit—not only successful demonstrations. Start with a narrow and measurable validation, then scale through evidence.
Is a free PoC necessarily better value?
It depends on the use case, data readiness and risk. Apply the principles and steps above, and make remaining uncertainty part of PoC acceptance.
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