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    Practical Examples Where AI and Machine Learning Are Supporting Businesses

Artificial Intelligence (AI) and machine learning are two words that seem to be on everyone’s lips. With the excitement about “just around the corner” self-driving cars, robots, and instant translators, it can be pretty challenging to see how exactly AI and machine learning support business and affect regular people’s lives in a particular moment. So how AI can help business?

A union of technological advancements in the fields of computing, artificial neural networks, statistical algorithms, and data analysis has driven the growth of AI and machine learning on an unparalleled scale. The phenomenon is speeding up exponentially, and it is no longer feasible for corporates and companies to ignore its underlying potential and the threats involved.

In this blog, we will take a look at five practical examples of how AI and machine learning have supported and helped businesses leverage the power of data to their advantage to enable faster decision-making, improve efficiency and increase productivity.

Let’s begin.

What Is AI and Machine Learning?

Artificial intelligence (AI) is an extensive subdivision of computer science concerned with building intelligent machines capable of performing tasks that typically require human beings’ assistance. AI is a science that has various approaches, but the developments in machine and deep learning create a shift in practically every sector of the technology industry.

How AI can help business is a popular topic in the tech industry these days. As you might have witnessed, AI is impacting the future of virtually every industry and every human being. It has and continues to act as the primary driver of emerging technologies such as robotics, big data, and the Internet of Things. AI will most likely continue to work as an innovator for the foreseeable future.

Examples of AI include:

  • Online check processing
  • Handwriting deciphering
  • Fraud detection by observing credit card spending patterns

Machine Learning and how AI can help business

In simple words, machine learning is an application of Artificial Intelligence that provides systems the ability to learn and develop from experience without being openly programmed. Machine learning involves the development of computer programs that can access data and use it to learn for themselves. It concentrates on software that learns from experience and improves their predictive accuracy as well as decision-making with time.

How machine learning can help business is also something companies today need to consider. The examples of machine learning are all around us. Self-driving cars and digital assistants like Alexa and Siri that search the web and play music in response to our voice commands are famous examples. Websites that recommend products based on what we bought, listened to, or watched before also use machine learning to make it happen. Robots that vacuum homes while we do something better with our time and spam detectors that prevent undesired emails from arriving in our inboxes are also based on the premise of machine learning.

Some countries, such as Switzerland, are currently operating at their peak and have become leading power global houses in AI and machine learning. Businesses must learn from their tech industries to stay relevant in this highly mechanized world.

AI and Machine Learning in Action: 5 Practical Examples from Different Industries

Let’s took a look at how AI and machine learning support businesses in different sectors and industries to drive greater efficiency, boost productivity, and enable faster decision-making based on data:

1. how AI can help business in Consumer Goods Sector

Several companies in the consumer goods sector have made use of AI and machine learning to leverage the power of data. We will look at three prominent examples:

Using machine learning and advanced analytics, Hello Barbie has introduced a new technology to listen and respond to children. A microphone is placed inside the Barbie doll’s necklace that records whatever the child says and transmits it to the servers at ToyTalk. The recording is then analyzed, and an appropriate response is selected from a collection of 8000 dialogues. Servers then send the correct response back to Barbie. All of this happens in just one second so the doll can respond to the child at once.

Coca-Cola is an international beverage company, the largest in the world, and highly popular in the global market. It has an extensive product list and operates in more than 200 countries, selling more than 500 drink brands. Considering the company’s scope, we can safely say that it generates a lot of data. To put this data into practice and analyze it, Coca-Cola has embraced a new technology that supports new product development, capitalizing on Artificial Intelligence (AI) robots. It has even started trialing augmented reality in bottling plants, and the launch is expected soon!

The Dutch company, Heineken, has been a global brewing leader for the last 150 years. To catapult its success, specifically in the United States, by leveraging the vast amount of data it collects, Heineken uses data-driven marketing and the Internet of Things to improve operations through data analytics. The company also makes use of AI augmentation and data-driven technology to improve not only its operations but also marketing, advertising, and customer service.

AI and machine learning support business

2. how machine learning can help business in Healthcare

The healthcare sector has also benefitted from the advancement in AI and machine learning. Several pharmaceutical companies and organizations in the healthcare sector are increasingly operating in several AI dimensions to leverage the power of data.

One such example is Infervision, a leading global high-tech enterprise specializing in medical Artificial Intelligence. Infervision uses AI and deep learning to save lives and diagnose cancer in China. There is a lack of radiologists in China to keep up with the demand of studying around 1.4 billion CT scans every year to look for lung cancer signs. Radiologists need to check a plethora of scans each day which is a very tedious task. It can cause human fatigue, which can lead to errors that the healthcare sector cannot afford. Hence, Infervision has derived and trained algorithms to supplement the work of radiologists to allow them to diagnose cancer more efficiently and accurately.

Another example of AI and machine learning being used to leverage data is the example of Google. Google’s DeepMind is an AI subsidiary based entirely on neuroscience. It depends on AI and machine learning advancements to develop machines that can mimic human brains’ thought processes. DeepMind has successfully defeated humans at games. Its opportunities for healthcare purposes, like reducing the time taken to plan treatments and using machines to diagnose ailments, are also really intriguing.

3. Creative Arts

Creative arts require a human touch. The human touch is what makes one piece of art stand out from another. However, this perception is changing rapidly as more individuals and companies are using AI and machine learning in the field of creative arts and gaining due success.

Let’s take a look at the AI-enabled Chef Watson cooking app from IBM that offers a glimpse of how AI can become a sous-chef in the kitchen and help develop recipes and advise human counterparts on food combinations to prepare unique dishes. By testing this app, researchers have seen that humans can create more in the kitchen while working with this app than working alone.

AI and machine learning can also augment creativity in the world of art and design. For instance, IBM’s machine learning system, Watson, was supplied several images of artist Antoni Gaudi’s work along with other relevant material to help the machine learn possible influences for his work. The system analyzed all the information and delivered inspiration to the human artists, who then created a sculpture in Antoni Gaudi’s style, as informed by Watson.

Machine learning and AI can also help musicians understand what their audiences want to hear so they can determine more accurately what songs can supposedly be hits. Music-generating algorithms are now very popular in the music industry and are inspiring new songs. The insights received from millions of conversations, newspaper headlines, and speeches can help create new music themes. IBM’s software called Watson BEAT uses AI and machine learning to develop different musical elements to inspire composers. It is smart enough to understand the whole composition of any music file.

4. AI and machine learning support business in Energy Sector

The energy sector is no stranger to machine learning and AI. Global energy leader British Petroleum (BP) is at the forefront of realizing the opportunities big data and AI have for the energy industry. The company uses technology to drive new performance levels, improve the use of resources and ensure the safety and reliability of gas and oil production and refining. BP has put data on engineers, scientists, and analysts’ fingerprints to ensure high performance levels by using AI technology, such as sensors that relay the conditions, at each of their sites to improve operations.

General Electric (GE) is another market leader attempting to deliver energy into the 21stcentury using big data, machine learning, and the Internet of Things to build an “internet of energy.” Advanced analytics, AI, and machine learning enable business optimization, operations, and predictive maintenance and power to help GE work toward a digital power plant’s vision.

5. Financial Sector

The financial sector is highly regulated, and companies in this sector deal with large amounts of highly sensitive data that need to be protected. But who can guarantee this protection and streamline operations? AI and machine learning, of course!

There are approximately 3.6 petabytes of data about individuals around the world. Experian PLC, the famous credit reporting agency, gets this massive amount of data from transactional records marketing databases and public information records. So how do they process this vast amount of data? Experian PLC actively embeds AI and machine learning into their products to enable quicker and more effective decision-making. These machines can learn to distinguish what data points are essential from those that aren’t and extract insights to optimize processes.

American Express is also a huge name in the financial sector that understands how AI and machine learning support business.  This financial services company processes transactions worth $1 trillion and currently has 110 million AmEx cards in operation. Hence, the company has to rely heavily on data analytics and machine learning to help detect credit card fraud to save millions in losses. Additionally, American Express has leveraged the power of data to develop apps that can connect cardholders with special offers and company products and services.

Final Words

All the world’s biggest tech giants are in a race to become the world leaders in AI and machine learning. These companies are trailblazers and embrace technology to provide top-notch products and services to their customers.

If you have a business and want to stay relevant in your industry in the years to come, you must not shy away from adopting the technology. Now that you know how AI can help business, along with machine learning, you must try to build the proper technical infrastructure that your company needs to support the development.

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