4 questions to answer before starting an AI project
A poorly framed AI project costs money and trust. The four core questions to answer before you begin.
AI is assumed to be good for every job; yet a poorly framed AI project costs money and trust. Answering four questions before you begin lets you start from the right place.
1. Which job, from whom, will it take over?
The job the AI will take over must be clear: which repetitive task, from which team, is it taking? A vague goal of 'help with everything' produces a result that cannot be measured or trusted.
2. What data will it work with?
A business assistant should speak from your data, not the whole internet. If the source — catalog, policy, document — is unclear, the output is unreliable too. If the data is not ready, it must be organized first.
3. When will it hand off to a human?
A good system knows its limits. It should hand cases it is unsure about, sensitive or special to a human. Without this handoff point, AI produces risk instead of trust.
4. How will we measure success?
- Which metric will improve: response time, resolved-request rate?
- Are real conversations reviewed regularly?
- How are wrong answers caught and corrected?
At APPTOIC we start AI projects by answering these four questions together; the goal is not an impressive demo but a system that genuinely lightens daily work and can be measured.
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