As an owner with zero coding knowledge, how should I evaluate software vendors who claim their platform uses AI to fix our operational bottlenecks so I do not get scammed by corporate theater?

Question

Tyler Smith · Accepted Answer

You do not need to understand Python, vector databases, or machine learning architectures to evaluate software. You only need to run the vendor through standard operational due diligence.

When a vendor pitches you an AI-powered solution, follow three strict rules:

- Force them to explain the operational improvement without using the words AI, algorithm, or intelligence. If they cannot describe the input, the transformation, and the business output in plain English, they are selling technological hype. Demand to see the raw operational workflow: what file enters the system, what exact business logic is applied, and what clean asset gets delivered to your team.
- Require a live demo on your messy data, not their polished sandbox. Vendors love demoing synthetic examples that run flawlessly. Hand them a batch of five real, unformatted invoices, messy job quotes, or complex client service tickets from last Tuesday. Watch how the software handles missing fields, typos, and format changes.
- Calculate the integration tax. Ask what happens when their tool fails. Does it silently break, or does it alert a specific seat on your team with an exception report? Ask who handles ongoing maintenance when third-party APIs update.

Remember the fundamental rule: never buy AI for the sake of having AI. Buy operational improvements where machine learning happens to run quietly in the background as a footnote. If the vendor cannot guarantee measurable operational throughput that improves your Scorecard numbers, walk away.