Machine Learning Applications for Every Industry

Machine Learning Applications for Every Industry

When people use the phrase machine learning, it’s often used synonymously with the umbrella term artificial intelligence or “AI.” 

Essentially, AI capabilities allow a computer to analyze vast amounts of information and data to arrive at a “reasoned” conclusion about the subject at hand, simulating the human decision process, often with better decisions being made.

Businesses in every industry have data that can provide meaningful insights into your organization. 

One successful application is with content matching and recommendations for streaming media, which is transforming the on-demand viewer experience. By analyzing user behavior, preferences, and more, streaming services can more accurately tailor recommendations and push targeted content with greater opportunity for monetization and engagement.

Virtually every other industry is or should consider incorporating AI into their business models. You do not need to be a large company to take advantage of AI. AI can help small and mid-sized businesses anticipate and fill customers product needs faster, improve inventory systems by incorporating Just in Time processes, reduce shipping and stocking errors, and facilitate the payment and collection process.

Some industries have embraced Machine Learning at a faster rate than others, here are a few use cases:


Due to the nature of the language these programs must parse, deep learning applications have been extremely useful in the legal industry. Legal phrasing can be complex and difficult to decipher, yet deep learning systems are already capable of analyzing tens of thousands of vital documents. When legal teams needed to dissect contract clauses that upset their or their client’s business and invoicing processes, they once had to manually review stacks of rigorously prepared documents. Now, legal professionals can feed them into a program that works far faster than any lawyer and that can pick out important phrases for further analysis by the legal team.

Food Retailers

Up to 40% of a grocer’s revenue comes from sales of fresh produce. So, to say that maintaining product quality is important is an understatement.

They are discovering that machine learning is the secret to smarter fresh-food replenishment. Grocery stores can train ML programs on historical datasets and input data about promotions and store hours as well, then use the analyses to gauge how much of each product to order and display. ML systems can also collect information about weather forecasts, public holidays, order quantity parameters, and other contextual information. They then issue a recommended order every 24 hours so that the grocer always has the appropriate products in the appropriate amounts in stock.

Businesses that implement machine learning in their replenishment workflows reduce their out-of-stock rates by up to 80%, along with up to 9% in gross-margin increases.

Media & Entertainment

Machine learning allows media companies to make their content more accessible to consumers through automatic captioning systems. Since implementing an automatic captioning program, YouTube has enabled 1 million functionally deaf Americans and 8 million hearing-impaired Americans to watch and enjoy its videos. As of 2017, its ML programs have become sophisticated enough to include captions for common non-speech audio, such as laughter and music, creating an even more complete experience for viewers.


Intelligent Tutoring Systems hold enormous potential for disrupting the classroom and helping students learn. These AI programs serve as virtual tutors, and they adapt their digital lessons based on each child’s strengths and weaknesses. Each time the student completes a task or quiz, a ML program processes that information to customize future materials.

By “learning” a user’s unique needs and identifying which types of lessons are most effective for them, the Intelligent Learing System helps the student overcome learning challenges and retain more knowledge. Research indicates that students who use intelligent tutoring systems perform better on tests than their peers who learn via large group instruction.


The development of smart applications and use of AI can reduce the number of tests an individual must take and help to decide the appropriate treatment. This reduces health care costs with potentially more accurate and lifesaving outcomes. Due to the high costs associated with health care and the significant benefits offered by better health care decisions, we are likely to see exponential growth in the application of AI to health care in the years to come.

Modern artificial intelligence is finally delivering on its promise to help consumers and businesses make better decisions and improve their quality of life. Small and middle market companies embracing AI today will have a competitive advantage in the marketplace.

If you are interested in exploring how machine learning can impact your specific organization, contact our application development team today. 

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