From the course: AI Strategy Foundations for Data Scientists and Team Leaders
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Understanding the AI strategy lifecycle
From the course: AI Strategy Foundations for Data Scientists and Team Leaders
Understanding the AI strategy lifecycle
Understanding the AI strategy lifecycle is important for team leaders implementing it. There are five critical parts of the lifecycle you need to know. First, start with the problem. What problems are you trying to solve? Define the business needs. Think about your organization's business model then think about the processes that AI could improve. You must leverage AI to augment, enhance and address these problems. Think of use cases. Common AI use cases include efficiency and productivity, risk management, time to market, revenue growth, increased accuracy and efficiency. This is by no means comprehensive, but a place to start. To help you narrow in on the key problems to solve, you need to interview stakeholders, both technical and business. It gives you a clear understanding of the business and technical problems. Second, identify opportunities. Look for the root of the business needs, the problems you identified. Look at your problem space. Consider this scenario. You fix the…
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