Getting on the AI learning curve
AI is likely to become one of the most important technologies of our era
After decades of promise and hype, AI is now seemingly everywhere. Over the past several years, the necessary ingredients have come together to propel AI beyond the research labs into the marketplace: Powerful, inexpensive computer technologies; huge amounts of data; and advanced algorithms including machine learning.
While AI is likely to become one of the most important technologies of our era, we’re still in the early stages of deployment, especially outside leading-edge technology companies. But, as AI continues its rapid progress, it’s not too early to ask a few important questions: What is AI’s overall value to the economy? What are the biggest application opportunities? What are AI’s most serious challenges and limitations?
To address these questions, McKinsey recently published a paper on the marketplace potential of AI. The paper is particularly focused on machine learning and related technologies, and is based on a detailed analysis of more that 400 use-cases across 19 industries and nine business functions.
“Two-thirds of the opportunities to use AI are in improving the performance of existing analytical use cases,” the paper says. This is a very interesting insight. AI is now being applied successfully to tasks that not long ago were viewed as the exclusive domain of humans — machine translation, natural language processing, defeating the world’s top Go players — but only 16% of the use cases studied by McKinsey are greenfield cases, in which only machine learning techniques can be used.
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