How Implementing Machine Learning Solutions Helps Your Business

Machine Learning for Business

Machine learning for business is the next great wave crashing in to create smarter and more efficient ways to handle business decisions and operations, as well as customer interactions. As with any business, the goal is to gather information from how the business is currently run. Then, an educated prediction is made about the data collected so that management and ownership can guide the company in a more successful direction.

Humans only have so much brainpower, and they tend to have disadvantages such as bias, poor pattern recognition, or even fatigue playing a role in their decision-making. With machine learning for business, none of these issues would hold back decisions. In fact, they would facilitate them even more so through the sheer size and scale of proper analysis that could be done with machine learning for business.

While most of the industry agrees on the general idea behind machine learning for business, each individual or company has its own spin on what it means for both them and the industry at large. This philosophical distinction between people involved in the industry leaves flexibility for machine learning for business to become whatever the industry needs it to be. Whether that focuses on simply navigating and gathering hard data or running algorithms to try to predict future trends, the possibilities are quite literally endless. Perhaps the most encouraging aspect of this growing technology is that it hasn’t even begun to be tapped to its full potential, and the ways machine learning for business can potentially be used is mind-numbingly massive.

 

Table of Contents

How Implementing Machine Learning Solutions Helps Your Business

Machine Learning Business Industries

Healthcare

Government

Internet Business

Transportation

Finance

Ways to Implement Machine Learning in Your Business Today

Chatbots

Decision-Making

Recommendation Engines

Pricing

Image Recognition

Information Recognition

Conclusion

 

Even though most people can agree on a basic definition of machine learning, there are different interpretations for the growing technology. The way Nvidia describes machine learning for business is to the point and can be understood by the general public. Nvidia says machine learning “is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world.”

As with any new path for technology or business in general, healthy skepticism and research must be taken on to protect the integrity of the industry. If you’re looking for backup confirmation of machine learning for the business being a vital implementation in business here and now, look no further than the Harvard Business Review. They are looking at some of the successful companies that use machine learning for business and looking at the industry as a whole.

Oftentimes, it can be difficult to know where exactly to start a new journey like machine learning for business. Once you can understand the basics and the foundation of machine learning, then you will naturally find your way to a greater depth of knowledge on the subject. Algorithms are a large part of machine learning, and bmcblogs lays out some of the top algorithms out there and their relationship to machine learning.

 

Machine Learning Business Industries

When making the effort to understand how and where machine learning for business will be making the greatest impact in the professional world, you must look at the industries that are already primed to bring in artificial intelligence to help them expand their data processing. Eventually, all sectors of industry can use machine learning for business, but there are certainly specific industries already ready for large-scale implementation at this time.

 

Healthcare

This is a sector that naturally comes to mind for most people when thinking about the future technology of machine learning for business. With all of the devices and gauges that gather data from patients, there are so many ways machine learning can squeeze into a niche in the healthcare industry. With enough study and time, maybe artificial intelligence can be used to predict diseases and perhaps even cancers years before they show any symptoms. The possibilities in healthcare are endless, but they are also encouraging for the health and safety of the human population, which brings a smile to anyone’s face.

 

Government

The massive amount of data that the government has to sift through on a daily basis for the simplest of tasks has to be near infinite. To have dedicated machine learning to wade through all the information will be crucial in finding the right information in a timely manner. A great application for artificial intelligence in the public sector would be predicting trends through the lens of all this data. Maybe things like import/export logistics, food distribution, federal aid, security, and other jobs the government has could help with a strong relationship between machine learning and the data the government stores.

 

Internet Business

Machine learning for business is primed to take on the difficulties of processing the data that an online business needs to attract its target audiences. Pair the e-commerce space with social media data and this artificial intelligence has two of the more powerful data collectors in existence to find who is most likely to buy your product and anything else you would potentially need to know about them.

 

Transportation

Transportation will be a massive issue that faces our country in the coming years. As the future changes, so will the way we move people from one place to another. No matter if it is public or private transportation, there will be a massive need for machine learning to help provide answers to efficiency problems and logistical problems. This could lead to an overhaul of our current road and red light system. Maybe the vehicles that we travel in would be changed completely. Perhaps even new ways to travel will be invented as machine learning guides us to find new ways to use the data.

 

Finance

Machine learning for business could end up taking the financial sector by storm if the people in charge figure out a reliable way to predict some of the trends that we see in the market. Prediction never has to be perfect, but as long as it makes some money for people, it will have longevity in the financial world. I would venture to say that where machine learning would really blast off would be related to insurance as it would allow insurance companies to better predict their yearly totals and therefore write more efficient policies for themselves. This doesn’t necessarily benefit the average business, but generally, most progress is good progress.

 

Ways to Implement Machine Learning in Your Business Today

Sometimes it can seem like real machine learning for business and perfected artificial intelligence is years or even decades away, but that is not the case. In today’s world, we already use some forms of machine learning, and they can be powerful tools to help your business.

Right now, I would say customer interaction is one of the most popular ways that machine learning for business is being implemented into the industry. According to Forbes, “57% of enterprise executives believe the most significant growth benefit of AI and machine learning will be improving customer experiences and support.” It makes sense that machine learning is sipping its toes into customer interactions largely at first, given the real importance of having a strong relationship between company and customer.

 

Chatbots

Chatbots have been around for years now. They pop up asking if they can help, and then have a set of questions and answer you can choose from. While it can be hard to find a specific question or answer you’re in need of, it does a solid job as a customer-facing FAQ. With advancements in machine learning, a business could take these simple chatbots and turn them into actual helpful customer service representatives over time, and I believe that is an end goal in the industry.

 

Decision-Making

As previously mentioned, machine learning for the business shines brightest when gathering data and then processing it through algorithms. Then they make decisions based on trends they can predict in the market or industry in general. These can be helpful for any company that needs to look at larger historical trends as a way to compliment their decision-making team. These large data sets can provide the human eye with more recognizable patterns, which can only help in making these long-term decisions.

 

Recommendation Engines

This is another type of machine learning that you experience in your daily life. Have you ever been scrolling on Instagram and noticed that you now have an advertisement for a product you searched on google? That’s where machine learning comes in to take your past interests and create recommendations based on similar interests. Sometimes these can be wildly off, but with enough data points, they can be bullseyes. They will take into account demographic data, past purchases, past searches, and create a profile about you to target your potential likes. This is a powerful tool for companies that are looking for specific customers, and the technology will only get more powerful and more accurate.

 

Pricing

Machine learning for business can even handle such important tasks as pricing your products and services based on the data it receives. The interesting part of this is that they can make small-scale tweaks to your pricing models based on the weather and the seasons, or something traditional like demand. Either way, the ability of the machine to recognize the need for these changes and to successfully process them simply through historical data sets is truly exciting for the future of business.

 

Image Recognition

With the ability of both humans and machines to alter images and pictures, we are in need of a way to properly verify images at all costs. Machine learning for business can do this for us. Something the everyday person would recognize would be the need for image recognition to prove that the image or video you are watching is unaltered and contains unaltered human faces. A more practical approach to image recognition would be a computer that can scan shelves to find instances of low or absent stock, ensuring that no one hides products from scanning, and the ability of these machines to detect unsafe or illegal activities. All of these potential uses would have a massive impact on the business world.

 

Information Recognition

In the same style as image recognition, information recognition would pertain to documents, both unofficial and legal. Documents such as tax information, legal contracts, etc. would be extracted through machine learning rather than risk humans making mistakes based on their abilities or perhaps their health on that particular day. As long as the industry doesn’t get in the business of having these machines interpret the documents, then it is a brilliant way to speed up these processes. Having the machines to transfer this data not only for current use, but future use in larger data set and algorithms would be extremely helpful in learning more about ourselves as a people and a country.

 

Conclusion

Machine learning for business will become a more and more integral part of the business industries as we progress further and further into the future. While there are some questions that still need to be answered on the topic, the general progression of this technology is promising. As machine learning bubbles to the surface and more and more businesses are persuaded by the ways they can be helped, the importance of getting a headstart now is priceless. An even greater part of this aspect of new technology is that it can help your business grow and identify pain points that you previously didn’t even recognize. Your company can then take action and advance the business with the help of machine learning.

There is a multitude of industries within which you can implement this artificial intelligence. In fact, you could find a home for machine learning in any company you wanted to. The accuracy with which data can be taken and transformed into historical trends and future predictions is truly industry-evolving. Anytime you have less guesswork involved in business decisions, you have more accurate solutions and less of a chance to massively miscalculate.

At the end of the day, the most important aspects of keeping your business afloat are understanding trends. These trends come in the form of the past, present, and future. Having the ability to not only recognize these trends but be in the first wave of a successful new trend provides your company with many benefits and potentially more opportunities in the future. All it takes is an open mind and a willingness to take on this new industry wave head-on.

 

 About the Author

Jeff Nelson AKA “the Relatable CTO”; has helped countless people leverage technology to better human productivity and help them achieve their goals.

Jeff is the Co-Founder and Chief Technology Officer of Blavity Inc, the leading company for Black culture and millennials, and the Founder and CEO of Cinchapi Inc., a real-time software platform for data discovery, analytics, and automation. His companies have combined to raise over $13 million in venture funding, generated millions in recurring revenue, and created dozens of jobs for women and underrepresented people.

Jeff’s expertise as a technical architect, software expert, and serial entrepreneur helps him drive innovation in technology, business, culture, and public policy. His technology consulting and software development expertise to create elegant solutions to complex problems using the latest technology, such as creatively harnessing the power of human and machine intelligence to make it easier for people to connect, work and thrive.

Jeff currently resides in Atlanta Ga with his family. In his spare time, he’s working on a new work -life-framework called High-Intensity Interval Productivity (HIIP). He enjoys playing golf and watching baseball while occasionally dabbling in interior design. Jeff has a B.S. in Computer Science from Washington University in St. Louis.

Jeff Nelson

Jeff Nelson

Jeff Nelson is a technical architect, software expert, and serial entrepreneur. With his extensive knowledge of software development and his ability to bring theoretical concepts to life, Jeff is driving innovation in technology, business, culture, and public policy. He is the Co-Founder and CTO of Blavity Inc., the leading company for Black culture and millennials, and the Founder and CEO of Cinchapi Inc., a real-time software platform for data discovery, analytics, and automation.

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