Twelve questions for any credit union AI consultant
Each of the twelve questions from the guide expanded into: why it matters, the follow-up to ask, what a strong answer includes, and the red flag that should end the conversation.
What share of your current engagements are with credit unions?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
Walk me through your last credit union engagement end to end. What did you leave behind?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
What would an NCUA examiner ask about the system you are proposing, and what documentation would we show them?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
Why should our first project be this one and not something else?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
What do you need from our data before you can commit to an outcome?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
Do you receive any compensation from vendors you recommend?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure. Evasive answers on questions 6 and 10 end the conversation.
Who exactly will do the work, and how much of their time do we get?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
Where in the statement of work does capability transfer appear? Show me the deliverable language.
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
What is the smallest engagement you will take, and what does it deliver?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
Describe a project of yours that failed and what you changed afterward.
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure. Evasive answers on questions 6 and 10 end the conversation.
How do you price: fixed scope, time and materials, or retainer, and why?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
If we build an internal AI team within two years, how does your role shrink?
Good answers share a texture: specific, quantified, comfortable with constraints, and unafraid of the questions about money and failure.
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