How do I evaluate AI vendors and platforms?
Quick Answer
Evaluate AI vendors across six dimensions: technical capability and fit with your use case, data security and compliance posture, integration with your existing systems, pricing transparency and total cost of ownership, vendor stability and track record, and quality of support and documentation. Request proof-of-concept trials with your actual data rather than relying on marketing demonstrations.
Summary
Key takeaways
- Test vendors with your real data, not their curated demo datasets
- Assess total cost of ownership including integration, training, and ongoing fees
- Evaluate data security and compliance credentials thoroughly
- Check vendor stability, customer references, and quality of technical support
A Practical Vendor Evaluation Framework
Common Pitfalls in AI Vendor Selection
FAQ
Frequently asked questions
Shortlist 3 to 5 vendors for detailed evaluation. Evaluating fewer limits your perspective, while evaluating too many becomes unmanageable. Start with a longer list and narrow down based on initial capability and fit assessments.
Yes. Involving procurement early helps set expectations about evaluation timelines, contract terms, and budget approval processes. This prevents delays later when you have identified your preferred vendor but need weeks to complete procurement.
Negotiate for a trial period, flexible scaling terms, data portability rights, clear SLAs with penalties, and the ability to exit without excessive costs. Avoid multi-year lock-ins unless the discount is substantial and the vendor is well-established.
Very important. References from organisations similar to yours in size, industry, and use case provide the most relevant insight. Ask references specifically about implementation experience, ongoing support quality, and whether the vendor delivered on their promises.
For significant investments, running parallel PoCs with 2 to 3 shortlisted vendors using your actual data provides definitive evidence for the decision. The cost of parallel PoCs is small compared to the risk of choosing the wrong vendor for a large implementation.
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