Advanced Computing in the Age of AI|Monday, July 13, 2020
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Machine Learning Will Transform Business: How to Benefit 

This past year there was a major debate in tech media over the future of artificial intelligence in business. The battle centered on whether AI should be feared and whether it would put people out of jobs. For some, the answer was it definitely would. Others believed it definitely wouldn’t. It turned out to be a great topic for debate, largely because no one really knows the answer.

While discussions surrounding AI’s eventual overthrow of humanity can be fun and interesting, they often overlook the little revolutions happening right now.

As the debate centers on the future, AI is already doing a lot right now to help human employees do their jobs better and more efficiently, improving the customer experience. This current AI revolution comes in the form of machine learning, a market that’s already worth billions and is growing at an annual rate of nearly 20 percent.

What Is Machine Learning, and What Can It Do for Business?

Machine learning — a term that broadly covers any software that can learn through its own experience rather than rely on direct input from a user — has a variety of potential applications. It can not only process large amounts of data instantaneously, but also extrapolates useful insights from this data. This is especially revolutionary in business intelligence because it takes a task that used to require weeks to complete and performs it in a matter of moments.

And machine learning is only becoming more advanced. While it was initially used only to tell people what’s happening to their businesses, it now can recommend strategies for moving forward. Machines that were once analysts are now becoming strategists.

Companies are already building upon the power of machine learning. Take Retention Science, for instance, which uses machine learning to help e-commerce companies understand each individual customer and tailor marketing campaigns to improve retention. Likewise, DataRPM allows organizations to automatically discover hidden patterns and anomalies within data through a simple visual interface. By combining big data and machine learning, these companies provide insights they might never have been uncovered through traditional means.

Enterprise software companies must continually identify weak spots in their businesses and implement operational changes to stay competitive. These new tools give executives the analyses they need almost instantly. It may not sound as exciting as an AI takeover, but instantaneous analysis is a revolution in its own right.

Getting the Most Out of Machine Learning

Like any new tech, machine learning still needs the right people behind it to work properly. Here are a few things to keep in mind when employing this tool in your business:

  • Help it learn. Ensure you have a good grasp on the algorithm your machine uses, and continually refine it to optimize its learning ability.
  • Encourage employee buy-in. Teach employees how to understand and make use of these new predictions, otherwise the best analyses will be redundant. Show employees that machine learning results in tangible improvements so they can see its incentive in action.
  • Keep an open mind. It’s not just employees who must jump on the bandwagon. There are three stages to machine learning: description, prediction, and prescription. It’s easy for C-level officers to get comfortable with the first two stages, but the third often gets some pushback because it requires teaching an old dog new tricks. With machine learning, you have to trust the system — even if it might contradict traditional methods.
  • Don’t forget the human touch. While this tech can help with decision-making, it doesn’t negate the need for human interaction. Ensure someone regularly still calls or surveys customers. Machine learning should be a complement to understanding your customers, not a substitute for person-to-person communication and live feedback.
  • Use machine learning to directly help customers. Companies such as Amazon use sophisticated engines to improve customer recommendations, but more businesses should embrace similar technologies for their clients. Machine learning can improve the customer experience on the front end as well as the back, making recommendations and identifying common pain points to avoid.

Whether we welcome our new AI overlords in the future or not, one thing is clear today: Organizations can and should use the intelligence of big data to aid employees and improve the customer experience. And, for now at least, machine learning works best with the aid of a helping human hand.

TXZhouAbout the Author:

TX Zhuo is a managing partner of Karlin Ventures, an L.A.-based venture capital firm that focuses on early-stage enterprise software, e-commerce, and marketplaces. Follow the company on Twitter.

About the author: Alison Diana

Managing editor of Enterprise Technology. I've been covering tech and business for many years, for publications such as InformationWeek, Baseline Magazine, and Florida Today. A native Brit and longtime Yankees fan, I live with my husband, daughter, and two cats on the Space Coast in Florida.

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