The most expensive mistake in enterprise AI is starting without clarity. Here are the 12 questions every leadership team should answer before committing to an AI initiative.
Problem Definition (Questions 1–3)
- Can you state the problem in one sentence, with a specific and measurable outcome?
- Is this problem currently solved in a way that creates a baseline for comparison?
- Who owns this problem, and do they have authority to implement changes based on AI output?
Data Readiness (Questions 4–6)
- Do you have at least 12 months of historical data relevant to this problem?
- Is that data clean, labeled, and accessible in a format that can be processed?
- Do you have ongoing data collection processes that will feed the model post-deployment?
Organizational Readiness (Questions 7–9)
- Is there executive sponsorship at a level that can authorize workflow changes?
- Have you identified change agents in the affected business units?
- Do you have a plan for communicating AI decisions to affected employees?
Technical Readiness (Questions 10–12)
- Do you have the infrastructure to deploy and maintain a model in production?
- Do you have a feedback mechanism to detect model drift over time?
- Have you defined the criteria that would trigger a model rollback?
You don't need to answer yes to all twelve. But you need to know which ones are no, and have a plan to address them.
AI StrategyReadinessChecklistLeadership
Marcus Okafor
Strategy Director at Nivorius
Part of the Nivorius research and consulting team, focused on practical applications of AI in education and enterprise contexts.
