How large enterprises are implementing machine learning: 3 main use cases

The biggest machine learning use cases for large businesses all involve one factor: Customers.

How businesses can implement machine learning

Professionals within larger organizations (25,000 employees or more) are significantly more satisfied with their machine learning progress than employees in smaller companies (500 employees or less), according to Algorithmia's 2018 State of Enterprise Machine Learning study released on Tuesday.

The report surveyed 523 data science and machine learning professionals to learn how companies of different sizes are using machine learning technologies, said the release. Employees from larger companies were 300% more likely to consider their machine learning efforts "sophisticated" and 80% more likely to be "satisfied" or "very satisfied" with the progression of such efforts, in comparison to smaller companies, added the release.

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Some 92% of respondents from larger organizations said their organization's investment in machine learning has grown by at least 25% in the past year, said the release. Larger companies have been utilizing machine learning in three main ways: Increasing customer loyalty (59%), increasing customer satisfaction (51%), and interacting with customers (48%), according to the report. Larger companies appeared to focus mainly on the consumer's needs when it comes to machine learning projects, which may account for its success in those deployments.

Larger enterprises set their sights on data science to save money. Almost one half (48%) of employees in large organizations cited cost savings as a prominent use case for machine learning, said the release. Using machine learning to save money allows for more room to use the same technology for other endeavors.

However, large companies do have an immediate advantage over small companies in regards to machine learning, said the release. Big organizations have added a new category to their infrastructures, which they call the "AI Layer." This component is used to manage compute loads, automate deployment of machine learning projects, and offer tools for machine learning management, said the release.

"In 2018, large enterprise companies have an advantage when it comes to machine learning because they have access to more data, can continue to invest in big R&D efforts, and have many problems that machine learning technology can solve cost-effectively," says Diego Oppenheimer, CEO at Algorithmia, in the release.

The big takeaways for tech leaders:

  • Larger companies are 300% more likely to consider their machine learning efforts "sophisticated" than smaller companies. -- Algorithmia, 2018
  • Big organizations focus their machine learning efforts on the customer, using the tech to increase customer loyalty (59%), increase customer satisfaction (51%), and interact with customers (48%). -- Algorithmia, 2018

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