Machine Learning Industry Predictions: Expert Consensus

Daniel Faggella

Daniel Faggella is Head of Research at Emerj. Called upon by the United Nations, World Bank, INTERPOL, and leading enterprises, Daniel is a globally sought-after expert on the competitive strategy implications of AI for business and government leaders.

How to Apply Machine Learning to Business Problems 4

In July of 2016, we sent out a series of survey questions to past guests who have been featured on the Emerj podcast, including academic researchers, founders, and executives who are experts in the machine learning domain. In this article, we focus on responses to the following question:

“What industries do you believe to be most poised to take advantage of machine learning in a business context?”

We received 58 total responses from 30 researchers and executives (the survey structure allowed respondents to choose from one to four relevant response categories, with an average individual response rate of 1.93 chosen categories).

On the whole, the trend in responses aligns with what we might have predicted, based on previous proprietary editorials/research and external published media on the topic. For example, the apparent optimistic bent towards healthcare & pharmaceuticals, followed by eCommerce, aligns with CB Insights’ tracking of popular areas for artificial intelligence venture capital deals in 2016 (an exception is robotics, though this may be a domain “on the horizon”).

At the end of this article, we expand on insights received from our survey, specifically taking a closer look at trends in the industries where experts expressed the most optimism and touching on why some of these industries are more likely to be disrupted than others.

You’ll find an abbreviated version of our full infographic below.

machine learning industry predictions

Note: The data for this graphic is no longer available publicly and are only available for Emerj research members. This change was enacted in November 2018.

Key Takeaways:

1 – Healthcare/Pharma  (Total of 10 out of 58 responses, or 17% of total)

For the past few months, we’ve been covering trends in advances in machine learning and medical applications, and it’s not a huge surprise that medical was chosen as the number one up-and-coming industry by our pool of experts. From robotic “surgeons” to smart informational databases, the applications for machine learning are only  now beginning to be tapped by industry:

  • Coverage on machine learning in healthcare includes our latest interview with Catalia Health’s Cory Kidd, who touches on medical AI applications and discusses his company’s development of a social robot meant to promote adherence to prescribed medical regiments. We also recently interviewed Your.MD’s Matteo Berlucchi, who discussed bridging the healthcare services gap through a personal health assistant platform that’s reaching more than 70 countries.
  • No doubt that one of the reasons healthcare is a primed industry is due to immense amounts of data that have been collected (in 2011, the U.S. alone was estimated at 150 exabytes of collected healthcare data and growing exponentially). We recently took a closer look at some of the biggest sources for healthcare data at present.
  • The specific machine learning applications in healthcare are wide and varied, another reason the field is poised to benefit from new applications of machine learning technology in the coming years.
  • Immense amounts of data, a growing IoT ecosystem, and an abundance of potentially life-altering applications are reasons why we predict that venture capital investments in machine learning in healthcare will be big in 2017.

2 – eCommerce and Robots/Drones (Tied in second for most responses, each with 6 total, or 10 percent of total responses) 

  • eCommerce has been a fertile field for machine learning applications, not only due to relative ease in collecting data on consumers but also due to the low-hanging ROI for companies, from increased customer conversions to more targeted marketing opportunities. Predictive analytics and machine learning is playing a break-out role at the individual and population-levels of marketing, as well for product and service predictions and recommendations (also a trend that can be applied within the healthcare domain).
  • Chatbots have gotten more than their fair share of coverage this year, at use across industries from travel to finance to eCommerce. We recently highlighted 7 tangible chat bot use cases, including 1-800-Flowers “Gwyn” and the official fashion-oriented H&M chatbot.
  • Though Robotics was tied in our survey for second, it’s the dark sheep (so to speak) in terms of where machine learning investments have been made as a whole to-date; however, like healthcare there are an abundance of applications to be made in robotics and drone technology, many of which overlap with other industries like  healthcare and agriculture. You can read our coverage of machine learning in robotics to get a feel for where applications are trending now.

3 – Finance/Banking (Total of 5 responses, or about 9 percent of total)

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