Machine learning has become an important buzzword in business technology circles, but for the average business owner that phrase probably makes your eyes glaze over, and for some, it may induce angst. But it doesn't have to be so scary or inaccessible. In fact, learning a little can help your business run smarter, faster and more efficiently. At its core, machine learning just means a computer that can learn independent of explicit programming.
From marketing to customer service, businesses are finding ways to use machine learning to streamline operations. It's also become a strong presence in our everyday lives – facial recognition software, search engines and even Netflix all utilize machine learning to tailor a customer's experience. Sure, Luddites aren't going to invent new ways to use machine learning to improve their business. But there are several ways businesses can benefit from machine learning that already exists.
What is machine learning?
Essentially, machine learning occurs when an artificial intelligence (AI) program can analyze data and draw new conclusions that weren't previously programmed. Whether these conclusions are in the form of finishing a task, answering a question or completing an action, they constitute a form of learning.
This type of technology has changed the way some businesses operate. By automating certain processes, businesses have become more efficient and even lowered costs. For businesses, there are two basic ways machine learning can impact efficiency: by automating processes and by analyzing vast amounts of data that people wouldn't be able to comprehend.
Matt Michelson is the chief scientist for InferLink Corp., a research and development firm that handles government contract work focused on AI and machine learning development. For his team, machine learning can be used to automate mundane tasks, such as inputting data.
"You might be able to have an algorithm replicate what someone is already doing, but at the scale of a computer," he said in an email. "Someone might take paper receipts, scan them and then enter the values in a spreadsheet. Instead, an algorithm could learn to pull the values from the scanned receipts and enter it themselves. It can do it at a scale no human could, and it frees that person to do something else more mind intensive."
In addition to automating certain processes, Michelson said that machine learning can replicate a human task and reach a new conclusion, instead of just making that task more efficient. "In Evid Science, our algorithms read and understand the medical literature, and so they can find ways to compare medical therapies that humans haven't done before. In this case, the benefit isn't really about efficiency, it's that it would be impossible for a human to read so much content and make sense of it all," he said.
Through these two lenses, machine learning can change the way your business operates. The method behind achieving this goal, however, is more complicated. [Read related article: How to Get a Job in AI or Machine Learning]
How it works
Machine learning involves two main distinctions: supervised and unsupervised learning. According to AI Horizon, the difference between these two types of learning rests with the information the machine has about the data. In supervised learning, a programmer can label what data is right and wrong based on a desired outcome.
Michelson further describes supervised learning as giving "your algorithm more and more examples of what you want it to do. For instance, you give it pictures and say which are pictures of buildings versus not buildings, for an app."
In unsupervised learning, a programmer does not label any data and instead the machine must take in as much information as possible, analyze it and pick the best option. Michelson pegged this type of learning as analyzing vast amounts of data.
"The [learning] can come because your algorithm has access to more and more data, though not examples, over time. For instance, users rating products or simply [having] more access to volumes and volumes of text," he said.
There are other forms of learning and different classifications for them, like semi-supervised learning, decision trees or reinforced learning, but the two defined types provide a bit of background on two main types of machine learning.
The difference between AI and machine learning
These two terms are used almost interchangeably by business owners, but there is a slight distinction between AI and machine learning technology. Machine learning specifically refers to a machine's ability to learn on its own while AI is more of an umbrella term that refers to a program's autonomy when completing a task.
How is it used in business?
There are multitude ways that machine learning has found its way into business. As a technology that's changed fields ranging from marketing to cybersecurity, some businesses have harnessed the power that technology like machine learning can provide.
One area in which machine learning has begun to thrive is advertising. By gathering and analyzing user data, ad companies can optimize messages and tailor them directly to different consumer bases. Scott Teger, who runs platform operations and analytics for the advertising firm Mundo Media, said that optimizing ads would be nearly impossible without machine learning.
"I work in digital advertising," Teger said, "and with so much of the world doing things online, the enormous task of optimizing advertising would be nearly impossible without AI. AI helps with everything from fraud, ad quality, to customer success and so on."
Another aspect of machine learning in advertising is dealing with fraud. Teger said that Mundo Media spends as much time building fraud controls as it does building technology.
"We're entering an age where bots are prolific and even more sophisticated. Without machine learning, it would be a daunting task to quickly and correctly identify real people versus bots designed to behave like real people," Teger said. "This … affects everyone in the chain, because it artificially drives up the marketing costs for advertisers and brands, which fluffs up the cost of products for consumers."
Customer service has seen an explosion in machine learning and AI technology. Services, including chatbots and automated assistance, have been developed and provided to businesses to simplify customer service issues.
Artificial Solutions is the parent company of Teneo, a program that provides businesses with an AI customer service option. Andy Peart, chief marketing officer for Artificial Solutions, said that machine learning has made a major impact on a business's ability to make customer service problems more convenient.
"For too long, customer service has been relegated to a formulaic question-and-answer scenario that rarely leaves the customer satisfied and often doesn't solve the problem at hand," Peart said. "Common to marketers and growing in prevalence are intelligent conversational chatbots."
These chatbots have allowed businesses to cut costs while efficiently handling customers' routine queries.
Another way machine learning has been utilized by businesses is through detecting fraud. Riskified is an ecommerce fraud prevention company that evaluates transactions and determines whether they are fraudulent. Stephen Fidgeon, director of communications for the company, said that Riskified uses algorithms to analyze data.
"By feeding our algorithms huge amounts of data, we're able to determine fraud instantly," wrote Fidgeon in an email. "Fraudsters are advanced and ever evolving. They share tactics and successes, so legacy solutions that focus on a set of rules are easily outsmarted. The nature of machine learning means that we're able to evolve with them and stay ahead of their newest tactics."
This is one area where machine learning has been used to protect different businesses. Heightened security is another example of how machine learning can get ahead of a problem and stop it before it hurts a business.
There are many other ways machine learning can be helpful, in addition to what we've touched on here. Machine learning and AI has created a strong foothold in the business world. As the industry continues to expand, it may be worth considering how machine learning or AI could impact your own business.