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State of Machine Learning and AI – McKinsey 2017 Report

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State of Machine Learning and AI McKinsey 2017 Report

McKinsey Global Institute (MGI) recently published an article, How Artificial Intelligence Can Deliver Real Value To Companies, discussing the state of Machine Learning and Artificial Intelligence (AI) for the year 2017 and unfurnished a lot of statistics. The article included findings from a recent McKinsey Global Institute Study, and a discussion paper, Artificial Intelligence, The Next Digital Frontier published in June.

For the study, McKinsey carried out interviews of more than 3,000 senior executives on the usage of AI technologies, and how their companies plan on deploying them in the near future. They also asked them about how AI can impact individuals, markets and governments. The institute also utilised McKinsey Analytics for the study and discussion paper.

Here are some of the key points that the study highlighted:

current ai wave

Source: Forbes

AI is turning into a hot race for patents and intellectual property (IP): According to the study, AI has turned into a hotbed for large companies with big companies fighting out the patent and IP battle. The study found out when it comes to publicly available data, M&A category grew the fastest by 85 per cent from the year 2013 to 2016. The report gives example of how some of the biggest auto manufacturers in the world like Toyota, Tesla and BMW are investing their money in robotics and machine learning for using in driverless cars.

Early Adopters of machine learning and AI: The study discovered that telecom, financial services and high tech are some of the early adopters of Machine Learning and AI. These early adopting industries have earned a reputation of investing big bucks in new technologies that can help them gain competitive edge over their peers.

ai adoption

Source: Forbes

Netflix is a big gainer: The report found out that online streaming service Netflix has been able to churn out some impressive results from the algorithm it employees to personalize recommendations to its 100 million subscribers all around the world. The company had discovered that on an average, a user ends up spending up to 90 seconds on searching a movie. Netflix uncovered that they have successfully been able to avoid subscription cancellations amounting to $1B annually by improving their search results.

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Amazon gained some good results from its $775 million acquisition of Kiva: According to the MGI study, the acquisition of Kiva, the robotics company that deals with automating picking and packing has helped Amazon in churning out some remarkable results. The study found out that the “Click to ship” cycle time, which earlier ranged from 60 to 75 minutes with humans, has fallen drastically to 15 minutes with Kiva acquisition. Further, the operating costs fell by an estimated 20 per cent, giving Amazon a return of almost up to 40 per cent on the original investment it made. The ecommerce site has also ended up increasing the inventory capacity by 50 per cent.

Tech giants spent big money on AI acquisitions: According to the study, tech biggies like Baidu and Google have spent anywhere between $20B to $30B on AI last year, with 90 per cent of this money being invested on R&D and deployment, and 10 per cent on AI acquisitions. The study highlighted that the current rate of AI investment is almost three times than the external investment growth witnessed since 2013.

Early adopters of AI: The study found out that professional services, healthcare, financial services are some of the greatest adopters of AI and have witnessed celebratory profit margins. According to the study, firms that enjoy senior management support for AI initiatives have invested capital in infrastructure to support its scale and have clear business aims end up minting out about 3 to 15 percentage point higher profit margin than regular firms.

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McKinsey estimates that total annual external investment in AI was between $8B to $12B in 2016: According to the study, AI saw a total annual external investment between $8B to $12B last year, with machine learning raking in nearly 60 per cent of that investment.

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