“15 Smart Ways Machine Learning Helps Businesses And Entrepreneurs”
Sept 11. 2019
POST WRITTEN BY
Expert Panel, Forbes Technology Council
Successful CIOs, CTOs & executives from Forbes Technology Council offer firsthand insights on tech & business.
Among the most impressive new developments in technology is the field of machine learning (ML). In essence, machine learning teaches an artificial intelligence system to teach itself. While this might sound like the start of a campy sci-fi horror story, the results are quite promising for small business.
Machine learning allows an entrepreneur to do many more tasks with the time they have to dedicate to the market, and results in significantly better efficiency when it comes to running the company. Below, 15 professionals from Forbes Technology Council explain how ML can benefit businesses and why entrepreneurs should be eager to adopt it as part of their plans.
1. Helping You Do More With Less
Machine learning drives down the cost of prediction, and prediction is rooted in all business decisions. Machine learning can help entrepreneurs and business owners fundamentally change operational models, through cheap predictions. Where previous revenue growth may have variable costs associated, due to more decisions being required, ML can be applied to help businesses scale with less. - Shawn Harris, zebra.com
2. Automating Routine Tasks
When everyone is talking about the lack of IT talent, machine learning can become your indispensable team member. Machine learning can empower you to automate routine IT tasks like security monitoring, auditing, data discovery and classification or reporting, so that the team can focus on the more strategic tasks you have always wanted to do, but never had an opportunity. - Ilia Sotnikov, Netwrix
3. Finding Areas To Maximize Efficiency
The first thing is to not get caught up in the hype. Start out looking at your organization and find areas where you have large data sets where you can apply ML to extract information to help your business maximize efficiency. Where can you remove needless touchpoints and manual tasks? This can help bring vital decision-making information to your teams, enabling them to really use ML. - Ernie Bray, AutoClaims Direct Inc. (ACD)
4. Managing Unstructured Data
So much of today's organizations are trying to manage growing volumes of unstructured data. Machine learning puts structure and meaning to that data quickly and efficiently to help inform decisions, investments, and strategies. - Chalmers Brown, Due
5. Gauging Risk More Effectively
Risk management is a complex business operation. There are countless variables to consider, and managers are forced to engage in complex decision-making with limited data. Machine learning offers a more complete understanding of a business's risk profile regarding fraud, errors, loss prevention and other liabilities. Machine learning tools can be tailored to the unique needs of the organization. - Monica Eaton-Cardone,Chargebacks911
6. Driving Strategic Business Advantage
While historical reporting focuses on “what happened,” ad-hoc analysis allows companies to answer “why it happened” and “what is happening now.” It is predictive modeling powered by machine learning that can answer the question of “what is going to happen next” and “what is the best that could happen.” Focus on building a data infrastructure to support this progression. - Pradeep Ittycheria, kasasa.com
7. Improving Personalization
From Google to Facebook, machine learning and AI are helping entrepreneurs spend their ad dollars more wisely. AI-driven targeting and insights are taking a lot of the guesswork out of where businesses should put their money, allowing marketers to get to know their target audience faster and better than ever before. -Dawson Whitfield, Looka (formerly Logojoy)
8. Solving Big Problems Humans Can't
Machine learning is ideally suited to help solve complex problems that humans can't, where data analysis can be streamlined. More data is zipping across data networks than anywhere else, but often remains untapped as a resource to improve user productivity. Applying ML- and AI-based technologies to understand how networked devices are behaving and performing delivers massive benefits. - Abe Ankumah, Nyansa
9. Speeding Up Research On What Customers Want
With machine learning getting cheaper by the day, it's becoming accessible to more and more people. Entrepreneurs and business owners can use machine learning to process customer data more efficiently. You'll know what type of users are more likely to convert into customers, what's the behavior of great customers. Predicting "related products" more accurately will help you increase revenue per customer. - Vikram Joshi,pulsd
10. Making Customer Engagement More Effective
Machine learning is a smart way to engage consumers or potential clients in a way that saves your employees time and collects valuable data. Use it to greet your business-to-business or business-to-consumer customers and save time while smartly gathering information. - Arnie Gordon, Arlyn Scales
11. Improving Marketing Efficiency
Machine learning has the ability to improve your marketing efforts by leaps and bounds. For instance, ML could predict customer profiles and send them more targeted, personalized messages. The more personalized the marketing message is to the individual, the more likely they will be to take notice and take action. -Thomas Griffin, OptinMonster
12. Predicting The Churn
Each and every business owner faces the challenging reality of customer churn. ML algorithms can help not only in predicting which customers are likely to churn in the near future, but also many of them have the capabilities of explaining the most important factors that lead to customer churn. - Pawel Rzeszucinski, Codewise
13. Detecting Trends
One of the best ways to use machine learning is to detect trends in a large data set that are not noticeable with a naked eye. For example, a lot of companies talk about trying to reduce bias in their hiring processes. Feeding all hiring data -- everything from resume review to interview feedback -- into an ML algorithm can paint a clear picture of the level of bias that exists in the process. - Tigran Sloyan, CodeSignal
14. Saving Time For Cybersecurity Workforce
Different cyber attack styles and threat levels often make it hard for algorithms to accurately predict a threat. However, as the volume of logged data increases, new solutions are being developed to improve predictive accuracy and increase the capability of the limited cybersecurity workforce. - Joseph Feiman, WhiteHat Security
15. Predicting Where The Market Is Moving
AI can be leveraged to predict where the market is moving and who those movers may be. It can also be used to identify potential key partners to strengthen your own position or to identify new threats. From an IP landscape perspective, it can be used to recommend what IP to license or create to either defend your position or attack the competition. - Jose Morey, Liberty BioSecurity