Google Cloud's Latest Research on Machine Learning: Adoption

In 1834, Charles Babbage invented an “all-purpose device that could be programmed with punched cards.” Less than a decade later, 27-year-old mathematician Ada Lovelace discovered a sequence of operations to solve equations using that device.

Now, machines do more than just solve equations, and they’re learning more every day, analyzing data, recognizing patterns, and transforming the way we do just about everything.

While Springer Research recently found the jury’s still out on whether we should use AI for things like writing textbooks, Google Cloud research confirms that it’s definitely useful when it comes to many aspects of running a business. Google Cloud is a pioneer in studying how we use machine learning, and how we’ll continue to use it in the future. In their newest report, Google Cloud shows off its research to demonstrate how machine learning is giving businesses a competitive advantage.

The first part of the report is concerned with the adoption of machine learning. Who is using it? How are they using it? And why should you consider it too?


All Aboard the AI Train

Google’s research shows that “the ML train is leaving the station, with most businesses on board.” They partnered up with MIT Technology Review to survey 375 business and technology leaders. 60% of those surveyed had already implemented a machine learning strategy. Another 18% said they plan to adopt strategies in the next year.


At What Cost?

36% of the early adopters are still in the early stages of adopting machine learning, which is understandable considering that the process requires a clear roadmap for handling data. That part may take time if your data management strategy is still uncertain, but the entire process is definitely worthwhile in the long run. Google’s global product marketing lead, Philippe Poutonnet, explains that “businesses are spending a lot of time in the data-gathering and data-preparation phases, as well as trying to figure out the data architecture.”

Just how much is it to invest in machine learning? Google Cloud and MIT found that only 26% of early adopters are devoting more than 15% of their IT budget to machine learning. Not bad considering that more than half of the respondents overall reported noticeable ROI for their efforts.


What For?

Hopefully those 5% uninterested in implementing machine learning change their minds, because research shows that businesses are using machine learning for “several key applications” like process automation and customer behavior analysis.

M-Brain and Google Cloud researched what industries are using machine learning to their advantages. The most popular results were healthcare, financial servicing, manufacturing, retail, and media and gaming. The most popular specific uses for machine learning are security, risk, and fraud analysis as well as non-financial asset management, and predictive analytics.


Why Wait?

The ML Express is filling up fast, and as one billion-dollar real estate CIO put it, “the sky’s the limit here. There is almost nothing we do that can’t benefit from [machine] intelligence and learning capabilities.”

Stay tuned for next week’s article to learn more about how machine learning is revolutionizing industries one at a time.

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