Marketing language is not an evaluation method
Credible leaders move the conversation from impressive outputs to the conditions under which those outputs can be trusted.
The four-question reality check
- Which model or AI technique does the product use for this task?
- What data grounds the output, and what data leaves our environment?
- How was quality measured on work that resembles ours?
- What happens when the system is wrong, and who is accountable?
Listen for operational answers
Strong answers describe test conditions, limitations, review steps, data handling, and escalation paths. Weak answers return to broad claims about intelligence or productivity.
The goal is not to disqualify every imperfect system. It is to understand the tradeoffs well enough to design a responsible use case.
Put it into practice
Use the four questions in your next demo and write down what evidence you would need before moving from interest to a pilot.