Researchers asked 375 business and technology leaders from a variety of organizations about their use of machine learning (ML). Of these respondents, 60 percent have already implemented a ML strategy, while another 18 percent plan to do so in 12 to 24 months. Only 5 percent reported no interest in ML technology and no plans to adopt it.
This doesn’t mean that a large majority of businesses have amassed teams of robots that could ace the Turing test, however. In a report on the new survey, Philippe Poutonnet, global product marketing lead for Google Cloud, explains that “Machine learning is basically a way for a computer to find the nuggets of information that a human can’t.”
While innovation-focused businesses, particularly those in the technology industry, may be further along in their ML strategies, Poutonnet says most companies are still unsure of how to approach ML. Even those using the approach may have incomplete strategies or be in the earliest stages of adoption.
This is what is keeping business
leaders awake at night: How to
harvest and make sense of their
data for competitive advantage.
“This is what is keeping business leaders awake at night: how to harvest and make sense of their data for competitive advantage,” Poutonnet says. “Businesses are spending a lot of time with the data-gathering and data-preparation phases, as well as trying to figure out the data architecture, and they don’t have time to play with the data itself,” he says.
However, for a computing discipline that’s still in its infancy, ML is already rewarding its enthusiasts with significant – and measurable – results, the survey suggests. More than half of respondents with ML projects said they can demonstrate ROI from their efforts, while 45 percent reported an increased number of insights due to more extensive data analysis. And 26 percent believe that ML has given their business a competitive edge.
Among survey participants with existing ML strategies, the most common projects involve text classification and mining, emotion and behavior analysis, and image recognition, classification, and tagging (each cited by 47 percent of respondents). Automated agents and bots top the list of priorities for the next year.
For more on how today’s businesses are applying and benefiting from machine learning access the complete report below.