This article explores the challenges organizations face when implementing AI solutions. It offers guidance on identifying suitable problems for AI, finding solutions when contexts don't perfectly align with AI's strengths, and selecting projects with the highest potential benefits for business or society. Drawing on expertise from Harvard Business School and Google DeepMind, the article sheds light on best practices for navigating the complexities of AI implementation.
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.
Artificial Intelligence AI Implementation Problem Solving Google Deepmind Business Strategy
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