Machine Learning Will Disrupt All Industries

December 12, 2018 - 7 minutes read

machine learning use cases

Machine learning is going to change every industry. Want to know how it will affect yours and how you can start using it? Download our Free Machine Learning Whitepaper right now!

Are you ready for the fourth industrial revolution? Here’s a secret—it’s actually already here. And at its core, one technology is driving the innovation: machine learning (ML).

Now, you may be wondering, “What is machine learning used for?” Well, we’re glad you asked! Machine learning is unlocking unprecedented value across every industry. In this post, we’ll cover how it’s transforming key sectors like transportation, healthcare, and manufacturing.

Taking Transit to the Next Level

Over the past few years, nothing has shaken up the transportation industry more than San Francisco-based ridesharing services like Uber and Lyft. But this will pale in comparison to the disruption that self-driving cars will bring. And machine learning is at the center of this road revolution.

machine learning use cases

Once Uber transitions to driverless cars, the company will go from earning only 20 percent of the revenue per ride to a full 100 percent, exponentially increasing its profit. But Uber’s far from the only one with its eye on autonomous vehicles. Waymo, a self-driving subsidiary of Alphabet Inc., has already amassed roughly 5 million miles of road testing—almost twice that of main competitors Tesla and Nvidia. This means that Waymo’s machine learning models have had substantially more time and experience to refine safety protocols and driving knowledge.

But cars are far from the only use of machine learning in transit. Airplanes and drones are also getting a boost in intelligence thanks to machine learning. Boeing is currently working on AI that is focused on reducing pilot input and human error on commercial flights. If this sounds scary to you, here’s a surprise: AI in the air is already happening! Major South Korean airline Asiana actually forbids pilots from flying the airplane once it surpasses an altitude of 3,000 feet. From then on, it’s all in the hands of AI.

Making Medicine More Intelligent

Wearable devices like the Apple Watch and Fitbit are already helping people live healthier lives by meticulously taking millions of data points about everything from sleep cycles to daily walking distances. But imagine what insights machine learning could offer by analyzing this data.

machine learning use cases

Behavioral changes are often the most effective (and cost-effective) way to stay healthy. And with machine learning algorithms to aid them, doctors will be able to predict future health complications before they occur, allowing patients to take proactive steps to avoid them. At the Georgia Institute of Technology, deep learning algorithms are already being utilized to predict heart failure before it happens.

This is far from the only benefit of machine learning in medicine. ML-powered computer vision technologies will give medical professionals unparalleled diagnosing capabilities. AI software can discover and deduce irregularities like tumors from X-rays and MRIs better than a human radiologist ever could. Stanford researchers have already built an algorithm capable of detecting 14 types of conditions from a single chest X-ray.

Manufacturing & Machine Learning

Maximizing efficiency while minimizing waste is the name of the game in manufacturing. Fortunately for this sector, that happens to be what machine learning is all about as well! Warehouses and facilities around the world are racing to employ machine learning in their supply chains, and for good reason. ML algorithms can eliminate inefficient bottlenecks, make inventory management seamless, and optimize the production and logistics of goods.

machine learning use cases

Of course, all of this will lead to greater profit margins. But machine learning will also cut lots of unnecessary costs. According to McKinsey, machine learning will reduce supply chain prediction errors by 50 percent. It will also eliminate transportation costs by 10 percent and administrative expenses by 40 percent.

Also, remember those autonomous vehicles we discussed? Machine learning will also make it possible for robots to operate in facilities for 24 hours a day, 365 days a year. This has many workers concerned about their future employment. But instead of eliminating jobs, machine learning will simply transform the jobs as we know them today. 78 percent of physical work could potentially be automated, enabling workers to take on safer, less physically stressful roles.

Brace for Impact

Delving into all industries that will be affected by machine learning would be impossible. But we hope you’ve enjoyed this short overview of what it will bring to transportation, medicine, and manufacturing. The cross-industry impact of machine learning cannot be overstated. Practically every business will feel its impact. And whether that’s positive or negative depends on how well an organization adopts ML.

machine learning use cases

Research from Accenture predicts that, by 2035, AI could increase profitability and productivity by 38 percent and 40 percent, respectively. PricewaterhouseCoopers believes that $15.7 trillion of GDP growth will be due to AI by the year 2030. That’s more than the current combined GDP output of India and China!

These figures are not surprising when considering the plethora of applications machine learning is perfect for. Machine learning offers two main benefits that any company would want: substantial improvement in customer satisfaction and a drastic reduction in operational costs. And as more organizations leverage machine learning’s capabilities, we’ll all soon realize that this technology isn’t only creating better business outcomes; it’s building a brighter, smarter future for us all.

Are you ready for machine learning?

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