This article explores the common hurdles organizations face when implementing AI, such as data scarcity, solution overload, and unclear objectives. Drawing on Google DeepMind's experience, it provides practical advice on identifying suitable AI applications, adapting solutions to imperfect contexts, and prioritizing projects with the greatest potential benefit for businesses or society.
While AI has the potential to solve major problems, organizations embarking on such journeys of often encounter obstacles. They include a dearth of high-quality data; too many possible solutions; the lack of a clear, measurable objective; and difficulty in identifying whether a proposed solutions is “good.” In tackling these issues, Google DeepMind, Alphabet’s AI lab that is striving to solve extremely challenging real-world problems, has come up with solutions that can benefit others.
In this article, we offer guidance to help organizations identify the right problems to address with AI, to find solutions when the context does not perfectly align with what AI is best at solving, and, after potential projects have overcome those hurdles, to choose those that can offer the largest benefits for business or for broader society.
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